+publisher:"University of Michigan" +contributor:("Noll, Douglas C.")

University of Michigan

1. Sarkar, Saradwata. Quantitative Assessment of Volume Change in Tumors Using Image Registration.

Degree: PhD, Biomedical Engineering, 2011, University of Michigan

URL: http://hdl.handle.net/2027.42/84652

► Assuming tumor volume change will be shown to be a biomarker for therapeutic response, accurate early quantification of tumor volume change could lead to interactively… (more)

▼ Assuming tumor volume change will be shown to be a biomarker for therapeutic response, accurate early quantification of tumor volume change could lead to interactively adapting an individual patient’s therapy such as drug or dose modification to achieve optimal response as well as shorter phase III clinical trials. Standard techniques for response evaluation like RECIST 1.1 or WHO measurement methods have limited effectiveness in accurately assessing small, early changes. Most current approaches estimate a tumor's change indirectly by independently segmenting it in interval exams and then subtracting the segmented volumes to obtain a change estimate. Ensuring the consistency of these independent segmentations across interval exams can be a significant challenge. This thesis develops a low noise, low bias direct algorithm to measure volume change using 3D image registration. Tumor pairs are spatially registered across intervals and volumetric change is calculated by summing local scale changes obtained from the Jacobian map of the deformation. Such an approach can also potentially show regions of differential growth and contraction across the lesion. The registration-based algorithm is evaluated using synthetic and in-vivo interval scans where true tumor volume change is unequivocally known. The 95% confidence error interval of measured volume change was (-8.93%, 10.49%) and (-7.69%, 8.83%) using mutual information and normalized cross correlation, respectively, as similarity measures for registration. To the best of this author’s knowledge, these are the tightest bounds reported thus far for zero-change in vivo studies. No statistically significant evidence of functional bias was found for the registration-based volume change measurement algorithm. Statistical models are developed to show that using the registration-based algorithm the error in measuring volume change increases with increase in tumor volume and decreases with the increase in tumor's normalized mutual information, even when that is not the similarity measure being optimized. The developed registration-based algorithm is also compared with other approaches to demonstrate that it has the potential to outperform indirect segmentation-based change measurement methods. The potential of an accurate registration-based change measurement algorithm in tracking progression of chronic obstructive pulmonary disease is also suggested through an initial study on a normal and a diseased patient. Advisors/Committee Members: Meyer, Charles R. (committee member), Fessler, Jeffrey A. (committee member), Kessler, Marc L. (committee member), Noll, Douglas C. (committee member).

Subjects/Keywords: Tumor Volume Change; Image Registration; Response to Therapy; Early Detection; Biomedical Engineering; Engineering

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APA (6^th Edition):

Sarkar, S. (2011). Quantitative Assessment of Volume Change in Tumors Using Image Registration. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/84652

Chicago Manual of Style (16^th Edition):

Sarkar, Saradwata. “Quantitative Assessment of Volume Change in Tumors Using Image Registration.” 2011. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/84652.

MLA Handbook (7^th Edition):

Sarkar, Saradwata. “Quantitative Assessment of Volume Change in Tumors Using Image Registration.” 2011. Web. 20 Jan 2021.

Vancouver:

Sarkar S. Quantitative Assessment of Volume Change in Tumors Using Image Registration. [Internet] [Doctoral dissertation]. University of Michigan; 2011. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/84652.

Council of Science Editors:

Sarkar S. Quantitative Assessment of Volume Change in Tumors Using Image Registration. [Doctoral Dissertation]. University of Michigan; 2011. Available from: http://hdl.handle.net/2027.42/84652

University of Michigan

2. Huh, Won Seok. Regularized Statistical Material Decomposition in Medical Imaging.

Degree: PhD, Electrical Engineering: Systems, 2011, University of Michigan

URL: http://hdl.handle.net/2027.42/86549

► In viewing underlying pathology with medical imaging, often specific material components contain most of the diagnostic information. Therefore, material component separation is desirable in many… (more)

Subjects/Keywords: Material Decomposition; Regularized Method; Electrical Engineering; Engineering

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APA (6^th Edition):

Huh, W. S. (2011). Regularized Statistical Material Decomposition in Medical Imaging. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/86549

Chicago Manual of Style (16^th Edition):

Huh, Won Seok. “Regularized Statistical Material Decomposition in Medical Imaging.” 2011. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/86549.

MLA Handbook (7^th Edition):

Huh, Won Seok. “Regularized Statistical Material Decomposition in Medical Imaging.” 2011. Web. 20 Jan 2021.

Vancouver:

Huh WS. Regularized Statistical Material Decomposition in Medical Imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2011. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/86549.

Council of Science Editors:

Huh WS. Regularized Statistical Material Decomposition in Medical Imaging. [Doctoral Dissertation]. University of Michigan; 2011. Available from: http://hdl.handle.net/2027.42/86549

University of Michigan

3. Khalsa, Kimberly A. Temporal Regularization Use in Dynamic Contrast-Enhanced MRI.

Degree: PhD, Biomedical Engineering, 2011, University of Michigan

URL: http://hdl.handle.net/2027.42/84566

► Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) studies demand both high spatial and high temporal resolution. We need high spatial resolution to accurately visualize tissue morphology,… (more)

▼ Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) studies demand both high spatial and high temporal resolution. We need high spatial resolution to accurately visualize tissue morphology, and we need high temporal resolution to accurately follow the contrast kinetics of the tissue, which provide clinically important physiological information. We can only acquire so many measurements per unit time, however, and this limited data implies an inherent tradeoff between spatial and temporal resolution in the reconstructed image sequence. Most existing methods undersample the data and then employ some sort of data sharing technique in the k-space domain to recover the ‘missing’ data points. These data sharing schemes are based on an implicit assumption that the dynamic object varies smoothly in time. We present an image reconstruction scheme based on an object domain model that does not attempt any k-space data recovery, but rather explicitly uses the assumption of temporal smoothness in the image domain to estimate the image sequence that best fits the available data. Our proposed method is called Temporal Regularization Use in Image Reconstruction (TRUIR), and is a penalized likelihood formulation that includes spatial and temporal regularization terms in addition to the data fidelity term. This work presents our TRUIR formulation for both single coil and parallel imaging, and explores various aspects of TRUIR reconstructed image sequences. We evaluate the effect of the spatial and temporal regularization parameters on the resolution properties of TRUIR reconstructed image sequences, and present our work toward establishing selection criteria for these parameters. In evaluating our proposed TRUIR method, we focus on the application of DCE-MRI in the characterization and assessment of breast cancer. Our simulation studies model contrast uptake in a dynamic digital breast phantom. Results show that TRUIR reconstructions offer improved temporal dynamics when compared to more traditional frame-by-frame reconstructions, as well as more accurate estimates of kinetic parameters, particularly when TRUIR is used in conjunction with two new proposed k-space sampling trajectories, which are also presented in this work. These new trajectories are also shown to be more robust to regularization parameter choice. Further work is needed to improve TRUIR’s spatial resolution. Advisors/Committee Members: Fessler, Jeffrey A. (committee member), Chenevert, Thomas L. (committee member), Gilbert, Anna Catherine (committee member), Noll, Douglas C. (committee member).

Subjects/Keywords: Image Reconstruction; Regularization; DCE-MRI; Breast Cancer; Biomedical Engineering; Electrical Engineering; Engineering

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APA (6^th Edition):

Khalsa, K. A. (2011). Temporal Regularization Use in Dynamic Contrast-Enhanced MRI. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/84566

Chicago Manual of Style (16^th Edition):

Khalsa, Kimberly A. “Temporal Regularization Use in Dynamic Contrast-Enhanced MRI.” 2011. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/84566.

MLA Handbook (7^th Edition):

Khalsa, Kimberly A. “Temporal Regularization Use in Dynamic Contrast-Enhanced MRI.” 2011. Web. 20 Jan 2021.

Vancouver:

Khalsa KA. Temporal Regularization Use in Dynamic Contrast-Enhanced MRI. [Internet] [Doctoral dissertation]. University of Michigan; 2011. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/84566.

Council of Science Editors:

Khalsa KA. Temporal Regularization Use in Dynamic Contrast-Enhanced MRI. [Doctoral Dissertation]. University of Michigan; 2011. Available from: http://hdl.handle.net/2027.42/84566

University of Michigan

4. Irwin, Zachary Thomas. Restoring Fine Motor Skills through Neural Interface Technology.

Degree: PhD, Biomedical Engineering, 2016, University of Michigan

URL: http://hdl.handle.net/2027.42/120648

► Loss of motor function in the upper-limb, whether through paralysis or through loss of the limb itself, is a profound disability which affects a large… (more)

▼ Loss of motor function in the upper-limb, whether through paralysis or through loss of the limb itself, is a profound disability which affects a large population worldwide. Lifelike, fully-articulated prosthetic hands exist and are commercially available; however, there is currently no satisfactory method of controlling all of the available degrees of freedom. In order to generate better control signals for this technology, and help restore normal movement, it is necessary to interface directly with the nervous system. This thesis is intended to address several of the limitations of current neural interfaces and enable the long-term extraction of control signals for fine movements of the hand and fingers. The first study addresses the problems of low signal amplitudes and short implant lifetimes in peripheral nerve interfaces. In two rhesus macaques, we demonstrate the successful implantation of regenerative peripheral nerve interfaces (RPNI), which allowed us to record high amplitude, functionally-selective signals from peripheral nerves up to 20 months post-implantation. These signals could be accurately decoded into intended movement, and used to enable monkeys to control a virtual hand prosthesis. The second study presents a novel experimental paradigm for intracortical neural interfaces, which enables detailed investigation of fine motor information contained in primary motor cortex. We used this paradigm to demonstrate accurate decoding of continuous fingertip position and enable a monkey to control a virtual hand in closed-loop. This is the first demonstration of volitional control of fine motor skill enabled by a cortical neural interface. The final study presents the design and testing of a wireless implantable neural recording system. By extracting signal power in a single, configurable frequency band onboard the device, this system achieves low power consumption while maintaining decode performance, and is applicable to cortical, peripheral, and myoelectric signals. Taken together, these results represent a significant step towards clinical reality for neural interfaces, and towards restoration of full and dexterous movement for people with severe disabilities. Advisors/Committee Members: Chestek, Cynthia Anne (committee member), Gates, Deanna (committee member), Noll, Douglas C (committee member), Stacey, William Charles (committee member).

Subjects/Keywords: Neural interfaces; Finger movement; Implantable devices; Biomedical Engineering; Engineering

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APA (6^th Edition):

Irwin, Z. T. (2016). Restoring Fine Motor Skills through Neural Interface Technology. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/120648

Chicago Manual of Style (16^th Edition):

Irwin, Zachary Thomas. “Restoring Fine Motor Skills through Neural Interface Technology.” 2016. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/120648.

MLA Handbook (7^th Edition):

Irwin, Zachary Thomas. “Restoring Fine Motor Skills through Neural Interface Technology.” 2016. Web. 20 Jan 2021.

Vancouver:

Irwin ZT. Restoring Fine Motor Skills through Neural Interface Technology. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/120648.

Council of Science Editors:

Irwin ZT. Restoring Fine Motor Skills through Neural Interface Technology. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/120648

University of Michigan

5. Chu, Alan. Simultaneous Multislice Functional Magnetic Resonance Imaging.

Degree: PhD, Biomedical Engineering, 2016, University of Michigan

URL: http://hdl.handle.net/2027.42/120669

► Functional magnetic resonance imaging (fMRI) is a valuable tool for mapping brain activity in many fields. Since functional activity is determined by temporal signal changes,… (more)

▼ Functional magnetic resonance imaging (fMRI) is a valuable tool for mapping brain activity in many fields. Since functional activity is determined by temporal signal changes, undesired fluctuations from physiological motion are problematic. Simultaneous multislice (SMS) imaging can alleviate these issues by accelerating image acquisition, increasing the temporal resolution. Furthermore, some applications require a temporal resolution higher than what conventional fMRI will allow. Current research in SMS has focused on Cartesian readouts due to their ease in analysis and reconstruction. However, non-Cartesian readouts such as spirals have shorter readout times and better signal recovery. This work explores the acquisition and reconstruction of both spiral and concentric ring readouts in parallel SMS. The concentric ring readout retains most of the benefits of spirals, but also increases the usability of alternative reconstruction techniques for non-Cartesian SMS such as generalized autocalibrating partially parallel acquisitions (GRAPPA). To date, non-Cartesian SMS imaging has only been reconstructed with sensitivity encoding (SENSE), but results in this work indicate GRAPPA-based reconstructions have reduced root-mean-square-error compared to SENSE and good subjective image quality as well. Furthermore, using point spread function analysis, the concentric ring trajectory is found to have superior slice separation properties compared to a spiral one. Since parallel imaging greatly magnifies the amount of data used for reconstruction, a novel coil compression method is developed, which outperforms conventional coil compression in fMRI, substantially decreasing the amount of reconstruction time needed for sufficient detection of functional activation. Results indicate that the proposed method can compress 3 simultaneous slice data using a 32-channel coil down to only 10 virtual coils without any adverse effects in functional activation, noise, or image artifacts. Competing methods require substantially more coils for preservation of the data, resulting in large reconstruction time savings for the proposed method. This work also explores the use of Hadamard-encoded fMRI for increased temporal resolution. Because Hadamard-encoded SMS uses data from multiple time frames to separate slices, physiological noise correction is critical. However, even with physiological noise correction, results indicate Hadamard-encoded fMRI is not as reliable as conventional fMRI due to undesired temporal fluctuations, most notably from uncorrected physiological noise. Advisors/Committee Members: Noll, Douglas C (committee member), Fessler, Jeffrey A (committee member), Nielsen, Jon-Fredrik (committee member), Peltier, Scott J (committee member).

Subjects/Keywords: magnetic resonance imaging; functional magnetic resonance imaging; simultaneous multislice; multiband; coil compression; Biomedical Engineering; Electrical Engineering; Neurosciences; Psychiatry; Radiology; Engineering; Health Sciences; Science

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APA (6^th Edition):

Chu, A. (2016). Simultaneous Multislice Functional Magnetic Resonance Imaging. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/120669

Chicago Manual of Style (16^th Edition):

Chu, Alan. “Simultaneous Multislice Functional Magnetic Resonance Imaging.” 2016. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/120669.

MLA Handbook (7^th Edition):

Chu, Alan. “Simultaneous Multislice Functional Magnetic Resonance Imaging.” 2016. Web. 20 Jan 2021.

Vancouver:

Chu A. Simultaneous Multislice Functional Magnetic Resonance Imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/120669.

Council of Science Editors:

Chu A. Simultaneous Multislice Functional Magnetic Resonance Imaging. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/120669

6. Aref, Abdulrahman. Improving Brain-Computer Interface Performance By Using Dynamic Methods Based on Analysis of Cognitive State.

Degree: PhD, Biomedical Engineering, 2018, University of Michigan

URL: http://hdl.handle.net/2027.42/144120

► Communication for individuals with severe motor and speech impairments can be very difficult and they find the need for the assistance of augmentative and alternative… (more)

▼ Communication for individuals with severe motor and speech impairments can be very difficult and they find the need for the assistance of augmentative and alternative communication (AAC) systems. Common commercialized AAC systems require some amount of voluntary control and are unusable by individuals with severe disabilities. Non-invasive brain-computer interfaces (BCIs) are an emerging means of communication for people with severe motor and speech impairments. BCIs allow the user to make selections on the computer just using their brain signals, electroencephalogram (EEG). However, although they are revolutionary for individuals that cannot control other available AAC systems, BCIs have several limitations. Two major limitations of BCIs are: 1) BCIs are static/synchronous in nature; 2) BCIs are susceptible to changes in user attention. Since people in the populations that need BCI technology the most (e.g. amyotrophic lateral sclerosis ;ALS) may experience attention impairments, incorporating attention-monitoring features into the BCI would improve BCI performance by reducing errors in these populations. This research presents two dynamic methods developed to help the BCI become more user-aware and allow users to control the BCI at their own pace. Using a well-established negative correlation between alpha band power in the EEG and attention, the first method used alpha band analysis to detect losses in user attention and abstained selections that were unattended to reduce potential errors. The second method, called P300-Certainty, abstained selections that do not reach a specified confidence level. To test both methods, off-line analysis was performed on recorded EEG from 30 subjects using the BCI for spelling. Subjects selected 9 sentences and at least 23 characters per sentence with additional corrections. Alpha band analysis and P300-Certainty were tested off-line, separately and together, on this dataset to determine their efficacy at increasing BCI accuracy by abstaining potential errors. In addition, P300-Certainty was implemented in a BCI-facilitated cognitive assessment to reduce potential errors, as well as, only choosing selections when they reach a specified confidence level. The on-line performance of P300-Certainty was calculated from this data. Alpha band analysis was performed off-line on this on-line data to determine its efficacy at increasing P300-Certainty on-line BCI accuracy. Alpha band power was shown to be significant between correct and incorrect character selections with a significance of p = 0.01004. Using this significance, alpha band analysis was used to classify selections as correct or incorrect based on the EEG, however it was only improved accuracy for a subset of subjects (subjects exhibiting high alpha variance). Off-line analysis of P300-Certainty was shown to increase accuracy from 82.01±12.59% to 88.82±8.85% by abstaining potential errors, with a statistical significance of p = 0.038. Furthermore, P300-Certainty and alpha band analysis used together, improved BCI accuracy, over… Advisors/Committee Members: Chestek, Cynthia Anne (committee member), Huggins, Jane Elizabeth (committee member), Stacey, William Charles (committee member), Noll, Douglas C (committee member).

Subjects/Keywords: Brain-Computer Interface; EEG; Attention; Biomedical Engineering; Engineering

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APA (6^th Edition):

Aref, A. (2018). Improving Brain-Computer Interface Performance By Using Dynamic Methods Based on Analysis of Cognitive State. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/144120

Chicago Manual of Style (16^th Edition):

Aref, Abdulrahman. “Improving Brain-Computer Interface Performance By Using Dynamic Methods Based on Analysis of Cognitive State.” 2018. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/144120.

MLA Handbook (7^th Edition):

Aref, Abdulrahman. “Improving Brain-Computer Interface Performance By Using Dynamic Methods Based on Analysis of Cognitive State.” 2018. Web. 20 Jan 2021.

Vancouver:

Aref A. Improving Brain-Computer Interface Performance By Using Dynamic Methods Based on Analysis of Cognitive State. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/144120.

Council of Science Editors:

Aref A. Improving Brain-Computer Interface Performance By Using Dynamic Methods Based on Analysis of Cognitive State. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/144120

University of Michigan

7. Holcombe, Sven. The Development of Population-Wide Descriptions of Human Rib and Rib Cage Geometry.

Degree: PhD, Biomedical Engineering, 2016, University of Michigan

URL: http://hdl.handle.net/2027.42/135879

► Elderly individuals, obese individuals, and females all have greater risk of rib fractures and other associated thoracic injuries than younger mid-sized male adults in motor… (more)

▼ Elderly individuals, obese individuals, and females all have greater risk of rib fractures and other associated thoracic injuries than younger mid-sized male adults in motor vehicle crashes. Differences in body morphology between these vulnerable populations and the subjects represented by physical or computational human body models is a potential source for this risk disparity, and efforts are required to quantify these differences in order to protect a wider population. We present a novel parametric shape model of the human rib centroidal path using logarithmic spirals. It provides a more accurate and efficient fit than previous models of overall rib geometry, and it utilizes direct geometric properties such rib size, aspect ratio, and "skewness" in its parameterization. The model was fitted to 21,124 ribs from 1000 adult CT scans, and regression analyses produced a flexible rib shape model to build ribs typical for any population of a given age, height, weight, and sex. Significant differences in rib shape were quantified across populations, and a new aging effect was uncovered whereby rib span and rib aspect ratio are seen to increase with age, producing characteristically shallower and flatter overall rib shapes in elderly populations. This effect was more strongly and directly associated with age than previously documented age-related changes in rib angulation. Simulated mechanical loading of ribs showed that the specific changes in shape found with age also had implications on their ability to resist deformation. Stiffness to body-anterior loading was seen to increase with age by up to 30% across a 70-year age difference. Finally, we place ribs into their appropriate thoracic context by building a similar parametric model of the surrounding skeleton. A modular approach is used that ensures accuracy in key geometric measures, and results show the accumulated effects on overall chest shape that come from individual variations in the ribs, spine, sternum, and their relative positions. This study can be used to help build population-specific computational models of the thoracic rib cage. Furthermore, results provide quantitative population corridors for rib shape parameters which can be used to improve the assessment and treatment of rib skeletal deformity and disease. Advisors/Committee Members: Grotberg, James B (committee member), Wang, Stewart C (committee member), D'Souza, Clive Rahul (committee member), Noll, Douglas C (committee member).

Subjects/Keywords: spiral; Biomedical Engineering; Engineering

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APA (6^th Edition):

Holcombe, S. (2016). The Development of Population-Wide Descriptions of Human Rib and Rib Cage Geometry. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/135879

Chicago Manual of Style (16^th Edition):

Holcombe, Sven. “The Development of Population-Wide Descriptions of Human Rib and Rib Cage Geometry.” 2016. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/135879.

MLA Handbook (7^th Edition):

Holcombe, Sven. “The Development of Population-Wide Descriptions of Human Rib and Rib Cage Geometry.” 2016. Web. 20 Jan 2021.

Vancouver:

Holcombe S. The Development of Population-Wide Descriptions of Human Rib and Rib Cage Geometry. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/135879.

Council of Science Editors:

Holcombe S. The Development of Population-Wide Descriptions of Human Rib and Rib Cage Geometry. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/135879

University of Michigan

8. Cao, Amos. Methods for Physiological Artifact Correction in Oscillating Steady State Imaging.

Degree: PhD, Biomedical Engineering, 2020, University of Michigan

URL: http://hdl.handle.net/2027.42/155132

► Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that provides an unparalleled ability to non-invasively study brain activity. Since its inception in the early… (more)

▼ Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that provides an unparalleled ability to non-invasively study brain activity. Since its inception in the early 1990s, fMRI has become a dominant tool in studying neurological responses to tasks and stimuli and has been critical in our evolving understanding of brain mapping. These achievements in neuroscience would not be possible without critical breakthroughs in MRI theory and hardware advancements, which continue to increase the speed and resolution of fMRI acquisitions. This dissertation explores a highly signal efficient fMRI imaging strategy known as Oscillating Steady-State Imaging (OSSI) and presents specialized artifact compensation strategies for addressing the practical challenges of the OSSI method. First, we develop analytical models and simulations of OSSI, which describe how the signal magnitude varies as a function of frequency. These simulations are then used to study how respiration-induced frequency changes cause artifactual signal fluctuations to a signal timecourse. Our simulations show that the severity of respiration artifacts changes with initial off-resonance. Furthermore, we show that respiration artifacts are primarily caused by transient signal effects rather than changes to steady-state magnitude. These findings inform the two correction strategies proposed in the remainder of the dissertation. The second portion of this work describes "OSSCOR," a retrospective method to correct timecourse magnitude changes caused by temporally varying frequency. We show how the OSSI signal exhibits a frequency-time duality which can be used to reshape structured physiological noise into a low-rank matrix. We then use principal component analysis in a data-driven correction strategy to create nuisance regressors for subsequent fMRI analysis. We show that free induction decay (FID) signals can also be used to create nuisance regressors in the same way in a variation of our method, referred to as "F-OSSCOR." Both OSSCOR and F-OSSCOR were found to significantly improve the functional sensitivity and signal stability compared to polynomial detrending alone. OSSCOR was also found to significantly outperform a standard data-driven correction method, CompCor. Finally, we present a prospective correction method which utilizes FID measurements to estimate and correct for B0 changes in real-time. Prospective correction has the potential to outperform retrospective correction methods by directly reducing perturbations to steady-state magnetization during acquisition. We first present the results of a feasibility analysis where simulation was used to determine how scan parameters would affect correction performance. We then developed a prospective correction application using a specialized scanner control platform to perform data analysis and parameter adjustment in real-time. Our initial fMRI proof-of-concept shows that real-time correction can increase the number of activated voxels and improve overall image stability as measured by tSNR. Advisors/Committee Members: Noll, Douglas C (committee member), Fessler, Jeffrey A (committee member), Nielsen, Jon-Fredrik (committee member), Seiberlich, Nicole (committee member).

Subjects/Keywords: functional MRI; steady-state imaging; Biomedical Engineering; Engineering

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APA (6^th Edition):

Cao, A. (2020). Methods for Physiological Artifact Correction in Oscillating Steady State Imaging. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/155132

Chicago Manual of Style (16^th Edition):

Cao, Amos. “Methods for Physiological Artifact Correction in Oscillating Steady State Imaging.” 2020. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/155132.

MLA Handbook (7^th Edition):

Cao, Amos. “Methods for Physiological Artifact Correction in Oscillating Steady State Imaging.” 2020. Web. 20 Jan 2021.

Vancouver:

Cao A. Methods for Physiological Artifact Correction in Oscillating Steady State Imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/155132.

Council of Science Editors:

Cao A. Methods for Physiological Artifact Correction in Oscillating Steady State Imaging. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/155132

University of Michigan

9. Simeth, Josiah. Quantifying Regional and Global Liver Function Via Gadoxetic Acid Uptake.

Degree: PhD, Biomedical Engineering, 2020, University of Michigan

URL: http://hdl.handle.net/2027.42/163264

► Liver function is a dominant factor in the survival of patients with hepatocellular carcinoma (HCC). Measures of regional and global liver function are critical in… (more)

▼ Liver function is a dominant factor in the survival of patients with hepatocellular carcinoma (HCC). Measures of regional and global liver function are critical in guiding treatments for intrahepatic cancers. Regional and global liver function assessments important for defining the magnitude and spatial distribution of radiation dose to preserve functional liver parenchyma and reduce incidence of hepatotoxicity from radiation therapy (RT) for intrahepatic cancer treatment. This individualized liver function-guided RT strategy is critical for patients with heterogeneous and poor liver function, often observed in cirrhotic patients treated for HCC. Dynamic gadoxetic-acid enhanced (DGAE) magnetic resonance imaging (MRI) allows investigation of liver function through observation of the uptake of contrast agent into the hepatocytes. This work seeks to determine if gadoxetic uptake rate can be used as a reliable measure of liver function, and to develop robust methods for uptake estimation with an interest in the therapeutic application of this knowledge in the case of intrahepatic cancers. Since voxel-by voxel fitting of the preexisting nonlinear dual-input two-compartment model is highly susceptible to over fitting, and highly dependent on data that is both temporally very well characterized and low in noise, this work proposes and validates a new model for quantifying the voxel-wise uptake rate of gadoxetic acid as a measure of regional liver function. A linearized single-input two-compartment (LSITC) model is a linearization of the pre-existing dual-input model but is designed to perform uptake quantification in a more robust, computationally simpler, and much faster manner. The method is validated against the preexisting dual-input model for both real and simulated data. Simulations are used to investigate the effects of noise as well as issues related to the sampling of the arterial peak in the characteristic input functions of DGAE MRI. Further validation explores the relationship between gadoxetic acid uptake rate and two well established global measures of liver function, namely: Indocyanine Green retention (ICGR) and Albumin-Bilirubin (ALBI) score. This work also establishes the relationships between these scores and imaging derived measures of whole liver function using uptake rate. Additionally, the same comparisons are performed for portal venous perfusion, a pharmacokinetic parameter that has been observed to correlate with function in patients with relatively good liver function, and has been used as a guide for individualized liver function-guided RT. For the patients assessed, gadoxetic acid uptake rate performs significantly better as a predictor of whole liver function than portal venous perfusion. This work also investigates the possible gains that could be introduced through use of gadoxetic uptake rate maps in the creation of function-guided RT plans. To this end, plans were created using both perfusion and uptake, and both were compared to plans that did not use functional guidance. While the… Advisors/Committee Members: Cao, Yue (committee member), Galban, Craig J (committee member), Hernandez-Garcia, Luis (committee member), Noll, Douglas C (committee member).

Subjects/Keywords: Liver Function; DCE MRI; Gadoxetic Acid; Generative Adversarial Network; Biomedical Engineering; Engineering

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APA (6^th Edition):

Simeth, J. (2020). Quantifying Regional and Global Liver Function Via Gadoxetic Acid Uptake. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/163264

Chicago Manual of Style (16^th Edition):

Simeth, Josiah. “Quantifying Regional and Global Liver Function Via Gadoxetic Acid Uptake.” 2020. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/163264.

MLA Handbook (7^th Edition):

Simeth, Josiah. “Quantifying Regional and Global Liver Function Via Gadoxetic Acid Uptake.” 2020. Web. 20 Jan 2021.

Vancouver:

Simeth J. Quantifying Regional and Global Liver Function Via Gadoxetic Acid Uptake. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/163264.

Council of Science Editors:

Simeth J. Quantifying Regional and Global Liver Function Via Gadoxetic Acid Uptake. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/163264

University of Michigan

10. Williams, Sydney. Constrained and Spectral-Spatial RF Pulse Design for Magnetic Resonance Imaging.

Degree: PhD, Biomedical Engineering, 2018, University of Michigan

URL: http://hdl.handle.net/2027.42/147647

► Magnetic Resonance Imaging (MRI) provides a non-invasive glimpse inside the human body, generates excellent soft tissue contrast, uses non-ionizing radiation, and has become a critical… (more)

▼ Magnetic Resonance Imaging (MRI) provides a non-invasive glimpse inside the human body, generates excellent soft tissue contrast, uses non-ionizing radiation, and has become a critical tool in diagnosis of disease in medicine. Radio Frequency (RF) pulses are an integral component of MRI pulse sequences and can be tailored to particular applications. This dissertation explores the MRI physics, convex optimization problems, and experimental methodologies required for the design of tailored RF pulses First, we introduce constrained RF pulse design, a process that incorporates meaningful, physical constraints, such as peak RF amplitude and integrated RF power, and enables efficient RF pulse design. With this process we explore simultaneous multislice (SMS) imaging, a method used to accelerate MRI and combat notoriously long acquisition times. Compared to an SMS pulse designed without constraints, our constrained pulses achieved lower magnitude normalized root mean squared error (NRMSE) for an equivalent RF pulse length, or alternatively, the same NRMSE for a shorter pulse length. Constrained RF pulse design forms a basis for the rest of the dissertation. Second, we show that prewinding pulses, a special class of RF pulses, help reduce signal loss due to intravoxel dephasing generated by magnetic field inhomogeneities. We propose a spectral-spatial prewinding pulse that leverages a larger effective recovery bandwidth than equivalent, purely spectral pulses. In an in vivo experiment imaging the brain of a human volunteer, we designed spectral-spatial pulses with a complex NRMSE of 0.18, which is significantly improved from the complex NRMSE of 0.54 in the purely spectral pulse for the same experiment. Finally, we consider a slab-selective prewinding pulse, that extends spectral and spectral-spatial prewinding pulses to a common 3D imaging method. Here we integrate optimal control optimization to further improve the slab-selective spectral pulse design and see an in vivo improvement of excitation NRMSE from 0.40 to 0.37. In the context of a steady-state sequence small-tip fast recovery (STFR), we also show a major reduction in mean residual transverse magnetization magnitude after the STFR “tip-up” recovery pulse from 0.18 to 0.02 when adding optimal control. This method has the potential to connect prewinding pulse design from the MRI physicist engineering workspace to a clinical application. In summary, we show that constrained RF pulse design provides an efficient way of improving MRI in terms of acquisition speed (via multislice imaging) and image quality (via signal recovery). Advisors/Committee Members: Fessler, Jeffrey A (committee member), Noll, Douglas C (committee member), Chenevert, Thomas L (committee member), Nielsen, Jon-Fredrik (committee member), Swanson, Scott D (committee member).

Subjects/Keywords: Magnetic resonance imaging; Radio frequency pulse design; Constrained optimization; Biomedical Engineering; Engineering

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APA (6^th Edition):

Williams, S. (2018). Constrained and Spectral-Spatial RF Pulse Design for Magnetic Resonance Imaging. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/147647

Chicago Manual of Style (16^th Edition):

Williams, Sydney. “Constrained and Spectral-Spatial RF Pulse Design for Magnetic Resonance Imaging.” 2018. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/147647.

MLA Handbook (7^th Edition):

Williams, Sydney. “Constrained and Spectral-Spatial RF Pulse Design for Magnetic Resonance Imaging.” 2018. Web. 20 Jan 2021.

Vancouver:

Williams S. Constrained and Spectral-Spatial RF Pulse Design for Magnetic Resonance Imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/147647.

Council of Science Editors:

Williams S. Constrained and Spectral-Spatial RF Pulse Design for Magnetic Resonance Imaging. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/147647

University of Michigan

11. Cha, Kenny. Computer-Aided Image Analysis and Decision Support System for Bladder Cancer.

Degree: PhD, Biomedical Engineering, 2017, University of Michigan

URL: http://hdl.handle.net/2027.42/140968

► Bladder cancer is a common type of neoplasm that can cause substantial morbidity and mortality among patients. Bladder cancer causes 16,870 deaths per year in… (more)

▼ Bladder cancer is a common type of neoplasm that can cause substantial morbidity and mortality among patients. Bladder cancer causes 16,870 deaths per year in the United States. It is expected that 76,030 new bladder cancer cases will be diagnosed in 2017. Multi-detector row CT (MDCT), and specifically MDCT when used for urography (CTU), has become the imaging modality of choice for evaluation of most urinary tract abnormalities. Interpretation of MDCT urograms that commonly exceeds 400 images. This is a demanding task for radiologists who have to visually track the entire upper and lower urinary tract and look for lesions that usually are small in size. Using a computer-aided diagnosis (CAD) system as an adjunct for the radiologist may reduce the number of lesions that are missed by the radiologists. To create a CAD system for detection of bladder lesions, we have developed methods and software to perform the following specific tasks: (1) segment the bladder; (2) detect bladder lesion candidates; (3) segment the bladder lesion candidates; (4) extract features from the segmented lesion candidates; (4) classify lesion candidates as true lesion findings or false positives using the extracted features; (5) detect bladder wall thickenings. Correct staging of bladder cancer is crucial in determining the need for neoadjuvant chemotherapy treatment and minimizing the risk of under-treatment or over-treatment. Also, reliable assessment of the response to neoadjuvant therapy at an early stage is vital for identifying patients who do not respond to this treatment and allows the physician to discontinue ineffective treatment and its undesired adverse effects on a patient’s physical condition. We have developed prototype predictive models for both bladder cancer staging and bladder cancer response to neoadjuvant treatment by adapting the methodology of feature classification that merges image-based biomarkers. The bladder lesion segmentation modules were used to extract the image-based biomarkers as input to the models. Early detection of bladder cancer, accurate tumor staging, and early prediction of treatment response could reduce mortality and morbidity, and improve quality of life for surviving patients. This dissertation presents the methods that we developed to automatically segment the bladder on CTU, and automatically detect masses and wall thickenings with sensitivity near 90% with a relatively low number of false positive findings. We have developed a system that distinguishes between muscle-invasive and non-muscle-invasive cancer, which is a clinical threshold used to determine treatment. We have also developed a system that uses the pre-treatment and post-treatment CTU scans to estimate the likelihood that the patient has fully responded to treatment. This system has achieved performance comparable to the radiologists, with area under the receiver operator characteristic curve (AUC) values in the range of 0.69 to 0.77. We performed an observer performance study where we saw that our system of predicting complete… Advisors/Committee Members: Fowlkes, Jeffrey Brian (committee member), Hadjiyski, Lubomir M (committee member), Fessler, Jeffrey A (committee member), Chan, Heang-Ping (committee member), Cohan, Richard H (committee member), Noll, Douglas C (committee member), Weizer, Alon Zadok (committee member).

Subjects/Keywords: Computer-Aided Diagnosis; Bladder Cancer; Machine Learning; Computer Vision; Biomedical Engineering; Engineering

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APA (6^th Edition):

Cha, K. (2017). Computer-Aided Image Analysis and Decision Support System for Bladder Cancer. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/140968

Chicago Manual of Style (16^th Edition):

Cha, Kenny. “Computer-Aided Image Analysis and Decision Support System for Bladder Cancer.” 2017. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/140968.

MLA Handbook (7^th Edition):

Cha, Kenny. “Computer-Aided Image Analysis and Decision Support System for Bladder Cancer.” 2017. Web. 20 Jan 2021.

Vancouver:

Cha K. Computer-Aided Image Analysis and Decision Support System for Bladder Cancer. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/140968.

Council of Science Editors:

Cha K. Computer-Aided Image Analysis and Decision Support System for Bladder Cancer. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/140968

University of Michigan

12. Muckley, Matthew J. Acceleration Methods for MRI.

Degree: PhD, Biomedical Engineering, 2016, University of Michigan

URL: http://hdl.handle.net/2027.42/120841

► Acceleration methods are a critical area of research for MRI. Two of the most important acceleration techniques involve parallel imaging and compressed sensing. These advanced… (more)

Subjects/Keywords: MR Image Reconstruction; Parallel MRI; Compressed Sensing; Low-rank Modeling; MRI Accelerations; Non-Cartesian MRI; Biomedical Engineering; Engineering

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APA (6^th Edition):

Muckley, M. J. (2016). Acceleration Methods for MRI. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/120841

Chicago Manual of Style (16^th Edition):

Muckley, Matthew J. “Acceleration Methods for MRI.” 2016. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/120841.

MLA Handbook (7^th Edition):

Muckley, Matthew J. “Acceleration Methods for MRI.” 2016. Web. 20 Jan 2021.

Vancouver:

Muckley MJ. Acceleration Methods for MRI. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/120841.

Council of Science Editors:

Muckley MJ. Acceleration Methods for MRI. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/120841

University of Michigan

13. Vazquez, Alberto L. The dynamics of the blood oxygenation response in functional magnetic resonance imaging.

Degree: PhD, Neurosciences, 2005, University of Michigan

URL: http://hdl.handle.net/2027.42/125529

► The objective of this work was to investigate the role of cerebral hemodynamics, particularly, cerebral blood flow (CBF), cerebral blood volume (CBV) and the cerebral… (more)

▼ The objective of this work was to investigate the role of cerebral hemodynamics, particularly, cerebral blood flow (CBF), cerebral blood volume (CBV) and the cerebral metabolic rate of oxygen consumption (CMR_O2), in neural activation and the generation of the blood oxygenation-level dependent (BOLD) response observed in functional magnetic resonance imaging (fMRI). A new magnetic resonance method based on the wash-in of unsaturated nuclear spins, referred to as AVIS (arterial vascular imaging by saturation), was developed to image the arterial vascular signal with good temporal and spatial resolution. This acquisition was sensitized to the arterial compartment for relatively short wash-in (or mixing) times. A functional imaging experiment that used the AVIS method showed the changes of the arterially dominated vascular response to be similar to the changes in CBF. Measurements of the arterial vascular changes play a very important role in cerebral hemodynamics because of its direct regulation of regional CBF. A known dependence of the BOLD response on the baseline CBF level was also investigated. Increases in the baseline blood flow level produce stimulation evoked CBF and BOLD responses that are slower and lower in amplitude. A vascular hemodynamic model in combination with CBF and BOLD fMRI data was used to characterize this dependence and determined that this effect is dominated by changes in the arterial blood flow time constant, and to a smaller extent by changes in the venous volume time constant of the model. Finally, the dynamic changes in CMR_O2 that take place as a result of evoked neuronal activity were estimated using CBF and BOLD data. Little is known about the dynamic coupling between the changes in neuronal function and CMR_O2. A model of the cerebral hemodynamics of neural activation estimated the temporal changes in CMR_O2 to be similar to those of the CBF changes. The time constant for the changes in CMR_O2 was estimated to be between 4 and 6 s. Models of the hemodynamics like the ones presented can be used to predict responses to different stimuli and different physiological conditions, in addition to improving on the information that can be extracted from BOLD data. Advisors/Committee Members: Noll, Douglas C. (advisor).

Subjects/Keywords: Cerebral Blood Flow; Dynamics; Functional Magnetic Resonance Imaging; Oxygenation; Response

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APA (6^th Edition):

Vazquez, A. L. (2005). The dynamics of the blood oxygenation response in functional magnetic resonance imaging. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/125529

Chicago Manual of Style (16^th Edition):

Vazquez, Alberto L. “The dynamics of the blood oxygenation response in functional magnetic resonance imaging.” 2005. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/125529.

MLA Handbook (7^th Edition):

Vazquez, Alberto L. “The dynamics of the blood oxygenation response in functional magnetic resonance imaging.” 2005. Web. 20 Jan 2021.

Vancouver:

Vazquez AL. The dynamics of the blood oxygenation response in functional magnetic resonance imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2005. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/125529.

Council of Science Editors:

Vazquez AL. The dynamics of the blood oxygenation response in functional magnetic resonance imaging. [Doctoral Dissertation]. University of Michigan; 2005. Available from: http://hdl.handle.net/2027.42/125529

University of Michigan

14. Lee, Gregory R. Functional magnetic resonance imaging with continuous arterial spin labeling: A novel pulse sequence and quantitative model.

Degree: PhD, Biomedical engineering, 2007, University of Michigan

URL: http://hdl.handle.net/2027.42/126755

► Arterial spin labeling (ASL) offers a number of advantages over the blood oxygenation level dependent technique for functional brain imaging. However, widespread adoption of ASL… (more)

▼ Arterial spin labeling (ASL) offers a number of advantages over the blood oxygenation level dependent technique for functional brain imaging. However, widespread adoption of ASL for functional imaging has been hampered by inferior SNR and temporal resolution. A novel pulse sequence, Turbo-CASL, allows acquisition of perfusion images with improved temporal resolution and increased sensitivity to neuronal-activity induced perfusion responses. It is demonstrated through both experiment and computer simulation that the technique is very sensitive to arterial transit time. This sensitivity is exploited to enhance detection of cerebral blood flow (CBF) changes in the presence of neuronal activation-induced reductions in transit time. By acquiring data at a range of timing parameters, the technique can also be used as a means of transit time measurement. One consequence of transit time sensitivity is increased difficulty in making quantitative measures of CBF under conditions of changing transit time. For this reason we propose a dynamic model which uses the transport equation to govern the arrival of labeled blood at the imaging plane. By incorporating time-varying velocity and CBF functions into the model, the resulting ASL signal was calculated under conditions of dynamic changes in these parameters. If the resting state transit time is known and a linear relationship between changes in CBF and mean arterial velocity is assumed, then CBF can be estimated from the measured ASL data. The assumption of a linear relationship for change in CBF versus mean arterial velocity was investigated by having subjects undergo four different tasks expected to invoke separate CBF response levels. By measuring both transit time and CBF under each of these conditions, it was determined that in humans there is a linear relationship between percentage changes in mean velocity and CBF at blood flow levels relevant to functional imaging experiments. Advisors/Committee Members: Noll, Douglas C. (advisor).

Subjects/Keywords: Arterial Spin Labeling; Cerebral Blood Flow; Continuous; Fmri; Functional; Imaging; Magnetic; Model; Novel; Pulse; Quantitative; Resonance; Sequence

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Lee, G. R. (2007). Functional magnetic resonance imaging with continuous arterial spin labeling: A novel pulse sequence and quantitative model. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/126755

Chicago Manual of Style (16^th Edition):

Lee, Gregory R. “Functional magnetic resonance imaging with continuous arterial spin labeling: A novel pulse sequence and quantitative model.” 2007. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/126755.

MLA Handbook (7^th Edition):

Lee, Gregory R. “Functional magnetic resonance imaging with continuous arterial spin labeling: A novel pulse sequence and quantitative model.” 2007. Web. 20 Jan 2021.

Vancouver:

Lee GR. Functional magnetic resonance imaging with continuous arterial spin labeling: A novel pulse sequence and quantitative model. [Internet] [Doctoral dissertation]. University of Michigan; 2007. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/126755.

Council of Science Editors:

Lee GR. Functional magnetic resonance imaging with continuous arterial spin labeling: A novel pulse sequence and quantitative model. [Doctoral Dissertation]. University of Michigan; 2007. Available from: http://hdl.handle.net/2027.42/126755

University of Michigan

15. Peltier, Scott James. Characterization and compensation of systematic noise in functional magnetic resonance imaging.

Degree: PhD, Pure Sciences, 2003, University of Michigan

URL: http://hdl.handle.net/2027.42/123456

► Functional magnetic resonance imaging (fMRI) has emerged as an important tool for noninvasive neuroscientific research. A limit to its effectiveness, however, is the presence of… (more)

▼ Functional magnetic resonance imaging (fMRI) has emerged as an important tool for noninvasive neuroscientific research. A limit to its effectiveness, however, is the presence of systematic noise that can obscure neuronal activation. Systematic noise in fMRI has a temporal and/or spatial structure, as opposed to additive random Gaussian white noise (e.g. thermal fluctuations). Several examples are low frequency signal drifts, head motion, physiological noise, and spontaneous neuronal events. These systematic noise sources are generally multiplicative and depend on the signal strength. As the fMRI signal is increased, by increasing voxel size or field strength, these noise sources may dominate the thermal noise, and determine the effective signal-to-noise ratio of a functional imaging experiment. Thus, understanding these noise sources and how to mitigate their effects is an important step in maximizing the potential of functional MRI as a neuro-imaging tool. This dissertation investigates characterization and compensation techniques for several types of systematic noise in fMRI. First, mitigation techniques for signal drift in single cycle MRI studies and physiological noise (caused by the respiratory and cardiac rhythms) are investigated, with functional contrast increased using appropriate noise compensation. Then, the effect of physiological noise in multi-shot imaging is explored. It is seen that the effective repetition time (TR) combines with the frequency of the physiological noise to modulate the level of physiological noise variance induced in a multi-shot study. A noise compensation process is next applied to a rapid, multi-slice acquisition and is shown to reduce noise variance down to the level of the associated single-slice case. Finally, resting state low frequency functional connectivity patterns are examined. Using a multi-echo sequence, they are shown to have the same T₂* and echo time dependence as normal task activation. A data-driven method of detecting functional connectivity patterns using a clustering algorithm is also investigated, and compared to the standard reference-based approach. Advisors/Committee Members: Noll, Douglas C. (advisor).

Subjects/Keywords: Characterization; Compensation; Fmri; Functional; Imaging; Magnetic; Resonance; Systematic Noise

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Peltier, S. J. (2003). Characterization and compensation of systematic noise in functional magnetic resonance imaging. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/123456

Chicago Manual of Style (16^th Edition):

Peltier, Scott James. “Characterization and compensation of systematic noise in functional magnetic resonance imaging.” 2003. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/123456.

MLA Handbook (7^th Edition):

Peltier, Scott James. “Characterization and compensation of systematic noise in functional magnetic resonance imaging.” 2003. Web. 20 Jan 2021.

Vancouver:

Peltier SJ. Characterization and compensation of systematic noise in functional magnetic resonance imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2003. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/123456.

Council of Science Editors:

Peltier SJ. Characterization and compensation of systematic noise in functional magnetic resonance imaging. [Doctoral Dissertation]. University of Michigan; 2003. Available from: http://hdl.handle.net/2027.42/123456

16. Lee, Benjamin Choong. Conditioning of and Algorithms for Image Reconstruction from Irregular Frequency Domain Samples.

Degree: PhD, Electrical Engineering: Systems, 2010, University of Michigan

URL: http://hdl.handle.net/2027.42/77912

► The problem of reconstructing an image from irregular samples of its 2-D DTFT arises in synthetic aperture radar (SAR), magnetic resonance imaging (MRI), computed tomography… (more)

▼ The problem of reconstructing an image from irregular samples of its 2-D DTFT arises in synthetic aperture radar (SAR), magnetic resonance imaging (MRI), computed tomography (CT), limited angle tomography, and 2-D filter design. The problem of determining a configuration of a limited number of 2-D DTFT samples also arises in magnetic resonance spectroscopic imaging (MRSI) and 3-D MRI. This work first focuses on the selection of the measurement data. Since there is no 2-D Lagrange interpolation formula, sufficient conditions for the uniqueness and conditioning of the reconstruction problem are both not apparent. Kronecker substitutions, such as the Good-Thomas FFT, the helical scan FFT, and the 45-degree rotated support, unwrap the 2-D problem into a 1-D problem, resulting in uniqueness and insights into the problem conditioning. The variance of distances between the adjacent unwrapped 1-D DTFT samples was developed as a sensitivity measure to quickly and accurately estimate of the condition number of the system matrix. A well-conditioned configuration of DTFT samples, restricted to radial lines in CT or spirals in MRI, is found by simulated annealing with the variance sensitivity measure as the objective function. The preconditioned conjugate gradient method reconstructs the 1-D solution that is then rewrapped to a 2-D image. In unrestricted cases, 2-D DTFT configurations like a regular hexagonal pattern can be unwrapped to uniformly-spaced and perfectly conditioned 1-D configurations and quickly solved using an inverse 1-D DFT. The next focus is on developing fast reconstruction algorithms. A non-iterative DFT-based method of reconstructing an image is presented, by first masking the 2-D DTFT samples with the frequency response of a filter that is zeroed at the unknown 2-D DFT locations, and then quickly deconvolving the filtered image using three 2-D DFTs. The masking filter needs to be precomputed only once per DTFT configuration. A divide-and-conquer image reconstruction method is also presented using subband decomposition and Gabor filters to solve smaller subband problems, leading to a quick unaliased low-resolution image or later to be recombined into the full solution. All methods are applied to actual CT data resulting in faster reconstructions than POCS and FBP with equivalent errors. Advisors/Committee Members: Yagle, Andrew E. (committee member), Fessler, Jeffrey A. (committee member), Noll, Douglas C. (committee member), Wakefield, Gregory H. (committee member).

Subjects/Keywords: Image Reconstruction; Conditioning; Noniterative; Subband Decomposition; Irregular Samples; Electrical Engineering; Engineering

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APA (6^th Edition):

Lee, B. C. (2010). Conditioning of and Algorithms for Image Reconstruction from Irregular Frequency Domain Samples. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/77912

Chicago Manual of Style (16^th Edition):

Lee, Benjamin Choong. “Conditioning of and Algorithms for Image Reconstruction from Irregular Frequency Domain Samples.” 2010. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/77912.

MLA Handbook (7^th Edition):

Lee, Benjamin Choong. “Conditioning of and Algorithms for Image Reconstruction from Irregular Frequency Domain Samples.” 2010. Web. 20 Jan 2021.

Vancouver:

Lee BC. Conditioning of and Algorithms for Image Reconstruction from Irregular Frequency Domain Samples. [Internet] [Doctoral dissertation]. University of Michigan; 2010. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/77912.

Council of Science Editors:

Lee BC. Conditioning of and Algorithms for Image Reconstruction from Irregular Frequency Domain Samples. [Doctoral Dissertation]. University of Michigan; 2010. Available from: http://hdl.handle.net/2027.42/77912

17. Jahanian, Hesamoddin. Functional MRI Using Pseudo-continuous Arterial Spin Labeling.

Degree: PhD, Biomedical Engineering, 2012, University of Michigan

URL: http://hdl.handle.net/2027.42/96080

► The widespread use of arterial spin labeling (ASL) for functional neuroimaging, has been hampered by its low signal to noise ratio (SNR) and poor temporal… (more)

▼ The widespread use of arterial spin labeling (ASL) for functional neuroimaging, has been hampered by its low signal to noise ratio (SNR) and poor temporal resolution. In this dissertation, we propose a novel method to optimize the SNR of pseudo-continuous arterial spin labeling (pCASL) technique. pCASL has been the most popular ASL method, however, in this study it is demonstrated through experiment and computer simulation that the SNR of this technique can be degraded due to off-resonance effects. The proposed method can effectively recover the lost SNR of pCASL using the B0 field map information. In our preliminary study the proposed method improved the inversion efficiency of the original pCASL by up to 56%. This method allows the use of pCASL in a wider range of conditions and applications, including real-time fMRI and ultra-high field MRI, where it may have otherwise been impractical. ASL is traditionally used for measurement of cerebral blood flow (CBF). In this dissertation we also develop a new framework for dynamic imaging of arterial blood volume (aCBV) utilized for functional brain imaging. This method employs the developed optimized pCASL technique, takes advantage of the kinetics of ASL signal and provides a signal, which is primarily determined by arterial blood volume with little or no contributions from the parenchyma. The proposed aCBV ASL approach has several important advantages over existing fMRI techniques. The temporal resolution of the developed aCBV ASL technique is approximately half of the temporal resolution of the conventional CBF ASL. We also found that the activation detection sensitivity of the aCBV ASL was by average 30% higher than that of the CBF ASL. Consequently, aCBV produced wider activated areas compared to CBF. The active areas in the aCBV map were also more focal compared to BOLD. Advisors/Committee Members: Hernandez, Luis (committee member), Noll, Douglas C. (committee member), Fowlkes, J. Brian (committee member), Zubieta, Jon K. (committee member).

Subjects/Keywords: Functional MRI; Arterial Spin Labeling; Off-resonance Correction; Biomedical Engineering; Engineering

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APA (6^th Edition):

Jahanian, H. (2012). Functional MRI Using Pseudo-continuous Arterial Spin Labeling. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/96080

Chicago Manual of Style (16^th Edition):

Jahanian, Hesamoddin. “Functional MRI Using Pseudo-continuous Arterial Spin Labeling.” 2012. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/96080.

MLA Handbook (7^th Edition):

Jahanian, Hesamoddin. “Functional MRI Using Pseudo-continuous Arterial Spin Labeling.” 2012. Web. 20 Jan 2021.

Vancouver:

Jahanian H. Functional MRI Using Pseudo-continuous Arterial Spin Labeling. [Internet] [Doctoral dissertation]. University of Michigan; 2012. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/96080.

Council of Science Editors:

Jahanian H. Functional MRI Using Pseudo-continuous Arterial Spin Labeling. [Doctoral Dissertation]. University of Michigan; 2012. Available from: http://hdl.handle.net/2027.42/96080

18. Al-Salem, Faisal M. Blind Super-Resolution from Multiple Undersampled Images using Sampling Diversity.

Degree: PhD, Electrical Engineering: Systems, 2010, University of Michigan

URL: http://hdl.handle.net/2027.42/77804

► Multiframe super-resolution is the problem of reconstructing a single high-resolution (HR) image from several low-resolution (LR) versions of it. We assume that the original HR… (more)

Subjects/Keywords: Non-parametric Multiframe Super-resolution; Engineering

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APA (6^th Edition):

Al-Salem, F. M. (2010). Blind Super-Resolution from Multiple Undersampled Images using Sampling Diversity. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/77804

Chicago Manual of Style (16^th Edition):

Al-Salem, Faisal M. “Blind Super-Resolution from Multiple Undersampled Images using Sampling Diversity.” 2010. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/77804.

MLA Handbook (7^th Edition):

Al-Salem, Faisal M. “Blind Super-Resolution from Multiple Undersampled Images using Sampling Diversity.” 2010. Web. 20 Jan 2021.

Vancouver:

Al-Salem FM. Blind Super-Resolution from Multiple Undersampled Images using Sampling Diversity. [Internet] [Doctoral dissertation]. University of Michigan; 2010. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/77804.

Council of Science Editors:

Al-Salem FM. Blind Super-Resolution from Multiple Undersampled Images using Sampling Diversity. [Doctoral Dissertation]. University of Michigan; 2010. Available from: http://hdl.handle.net/2027.42/77804

19. Panagis, Kathleen. Methods for Improving MRI-Based Conductivity Mapping.

Degree: PhD, Biomedical Engineering, 2017, University of Michigan

URL: http://hdl.handle.net/2027.42/144027

► The electrical properties - permittivity and conductivity - of a material describe how electromagnetic waves behave in that material. Electrical properties are frequency-dependent parameters and,… (more)

▼ The electrical properties - permittivity and conductivity - of a material describe how electromagnetic waves behave in that material. Electrical properties are frequency-dependent parameters and, for a liquid sample, are measured with a dielectric probe and a network analyzer. This measurement technique is not feasible in vivo, but methods have been developed to make these measurements using magnetic resonance imaging (MRI). This work focuses on measuring conductivity, or the ability to conduct electric current. Mapping the electrical properties within the human body can provide important information for MRI safety and diagnostic applications. First, the specific absorption rate (SAR) in an MRI scan is proportional to conductivity, and limited to minimize the risk of heating in a subject. Knowledge of subject-specific conductivity maps could lead to better, subject-specific SAR estimation. Second, several small studies in recent years have shown that conductivity is elevated in malignant tumors as compared to healthy tissue. There are open research questions regarding the correlation between conductivity and other diagnostic metrics. Both of these applications benefit from accurate conductivity maps. In this work we describe three different methods for improving the accuracy of conductivity maps. The first is a novel regularized, model-based approach which we refer to as the Inverse Laplacian method. The Inverse Laplacian method resulted in lower reconstruction bias and error due to noise in simulations than the conventional filtering method. The Inverse Laplacian method also produced conductivity maps closer to the measured values in a phantom and with reduced noise in the human brain, as compared to the filtering method. The second is a method for combining multi-coil MRI data for conductivity mapping, because the use of multi-coil receivers can drastically improve the SNR in conductivity maps. The noise in the combined phase data using the proposed method was slightly elevated as compared to the optimal combination method, but the conductivity uniformity in a uniform gel phantom was greater than that of the optimal combination method. Furthermore, by visual inspection, the human brain conductivity calculated from data combined using the proposed method had minimal bias and noise amplification. Finally, we present a method for mapping conductivity tensors, as opposed to scalar values, which provides an additional layer of information to conductivity maps. Our proposed mathematical framework yields accurate tensor quantities provided the object can rotate 90 degrees in any direction. However, restricting the object rotation to mimic the constraints on a human subject yields slightly inaccurate results. We also present a dictionary-based approach to tensor calculations to try to improve the tensor estimates using restricted rotations. Advisors/Committee Members: Noll, Douglas C (committee member), Chenevert, Thomas L (committee member), Fessler, Jeffrey A (committee member), Nielsen, Jon-Fredrik (committee member).

Subjects/Keywords: electrical property tomography; magnetic resonance imaging; Biomedical Engineering; Engineering

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APA (6^th Edition):

Panagis, K. (2017). Methods for Improving MRI-Based Conductivity Mapping. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/144027

Chicago Manual of Style (16^th Edition):

Panagis, Kathleen. “Methods for Improving MRI-Based Conductivity Mapping.” 2017. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/144027.

MLA Handbook (7^th Edition):

Panagis, Kathleen. “Methods for Improving MRI-Based Conductivity Mapping.” 2017. Web. 20 Jan 2021.

Vancouver:

Panagis K. Methods for Improving MRI-Based Conductivity Mapping. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/144027.

Council of Science Editors:

Panagis K. Methods for Improving MRI-Based Conductivity Mapping. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/144027

20. Matakos, Antonios. Dynamic Image and Fieldmap Joint Estimation Methods for MRI Using Single-Shot Trajectories.

Degree: PhD, Electrical Engineering-Systems, 2013, University of Michigan

URL: http://hdl.handle.net/2027.42/102449

► In susceptibility-weighted MRI, ignoring the magnetic field inhomogeneity can lead to severe reconstruction artifacts. Correcting for the effects of magnetic field inhomogeneity requires accurate fieldmaps.… (more)

▼ In susceptibility-weighted MRI, ignoring the magnetic field inhomogeneity can lead to severe reconstruction artifacts. Correcting for the effects of magnetic field inhomogeneity requires accurate fieldmaps. Especially in functional MRI, dynamic updates are desirable, since the fieldmap may change in time. Also, susceptibility effects that induce field inhomogeneity often have non-zero through-plane gradients, which, if uncorrected, can cause signal loss in the reconstructed images. Most image reconstruction methods that compensate for field inhomogeneity, even using dynamic fieldmap updates, ignore through-plane fieldmap gradients. Furthermore, standard optimization methods, like CG-based algorithms, may be slow to converge and recently proposed algorithms based on the Augmented Lagrangian (AL) framework have shown the potential to lead to more efficient optimization algorithms, especially in MRI reconstruction problems with non-quadratic regularization. In this work, we propose a computationally efficient, model-based iterative method for joint reconstruction of dynamic images and fieldmaps in single coil and parallel MRI, using single-shot trajectories. We first exploit the fieldmap smoothness to perform joint estimation using less than two full data sets and then we exploit the sensitivity encoding from parallel imaging to reduce the acquisition length and perform joint reconstruction using just one full k-space dataset. Subsequently, we extend the proposed method to account for the through-plane gradients of the field inhomogeneity. To improve the efficiency of the reconstruction algorithm we use a linearization technique for fieldmap estimation, which allows the use of the conjugate gradient algorithm. The resulting method allows for efficient reconstruction by applying fast approximations that allow the use of the conjugate gradient algorithm along with FFTs. Our proposed method can be computationally efficient for quadratic regularizers, but the CG-based algorithm is not directly applicable to non-quadratic regularization. To improve the efficiency of our method for non-quadratic regularization we propose an algorithm based on the augmented Lagrangian (AL) framework with variable splitting. This new algorithm can also be used for the non-linear optimization problem of fieldmap estimation without the need for the linearization approximation. Advisors/Committee Members: Fessler, Jeffrey A. (committee member), Noll, Douglas C. (committee member), Nielsen, Jon-Fredrik (committee member), Nadakuditi, Rajesh Rao (committee member).

Subjects/Keywords: Magnetic Resonance Imaging (MRI); Echo-Planar Imaging (EPI); EPI Ghost Correction; Joint Estimation; Through-plane Fieldmap Gradients; Augmented Lagrangian (AL); Electrical Engineering; Engineering

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APA (6^th Edition):

Matakos, A. (2013). Dynamic Image and Fieldmap Joint Estimation Methods for MRI Using Single-Shot Trajectories. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/102449

Chicago Manual of Style (16^th Edition):

Matakos, Antonios. “Dynamic Image and Fieldmap Joint Estimation Methods for MRI Using Single-Shot Trajectories.” 2013. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/102449.

MLA Handbook (7^th Edition):

Matakos, Antonios. “Dynamic Image and Fieldmap Joint Estimation Methods for MRI Using Single-Shot Trajectories.” 2013. Web. 20 Jan 2021.

Vancouver:

Matakos A. Dynamic Image and Fieldmap Joint Estimation Methods for MRI Using Single-Shot Trajectories. [Internet] [Doctoral dissertation]. University of Michigan; 2013. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/102449.

Council of Science Editors:

Matakos A. Dynamic Image and Fieldmap Joint Estimation Methods for MRI Using Single-Shot Trajectories. [Doctoral Dissertation]. University of Michigan; 2013. Available from: http://hdl.handle.net/2027.42/102449

21. Cho, Jang Hwan. Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography.

Degree: PhD, Electrical Engineering: Systems, 2014, University of Michigan

URL: http://hdl.handle.net/2027.42/110319

► Technological advances in CT imaging pose new challenges such as increased X-ray radiation dose and complexity of image reconstruction. Statistical image reconstruction methods use realistic… (more)

▼ Technological advances in CT imaging pose new challenges such as increased X-ray radiation dose and complexity of image reconstruction. Statistical image reconstruction methods use realistic models that incorporate the physics of the measurements and the statistical properties of the measurement noise, and they have potential to provide better image quality and dose reduction compared to the conventional filtered back-projection (FBP) method. However, statistical methods face several challenges that should be addressed before they can replace the FBP method universally. In this thesis, we develop various methods to overcome these challenges of statistical image reconstruction methods. Rigorous regularization design methods in Fourier domain were proposed to achieve more isotropic and uniform spatial resolution or noise properties. The design framework is general so that users can control the spatial resolution and the noise characteristics of the estimator. In addition, a regularization design method based on the hypothetical geometry concept was introduced to improve resolution or noise uniformity. Proposed designs using the new concept effectively improved the spatial resolution or noise uniformity in the reconstructed image. The hypothetical geometry idea is general enough to be applied to other scan geometries. Statistical weighting modification, based on how much each detector element affects insufficiently sampled region, was proposed to reduce the artifacts without degrading the temporal resolution within the region-of-interest (ROI). Another approach using an additional regularization term, that exploits information from the prior image, was investigated. Both methods effectively removed short-scan artifacts in the reconstructed image. We accelerated the family of ordered-subsets algorithms by introducing a double surrogate so that faster convergence speed can be achieved. Furthermore, we present a variable splitting based algorithm for motion-compensated image reconstruction (MCIR) problem that provides faster convergence compared to the conjugate gradient (CG) method. A sinogram-based motion estimation method that does not require any additional measurements other than the short-scan amount of data was introduced to provide decent initial estimates for the joint estimation. Proposed methods were evaluated using simulation and real patient data, and showed promising results for solving each challenge. Some of these methods can be combined to generate more complete solutions for CT imaging. Advisors/Committee Members: Fessler, Jeffrey A. (committee member), Noll, Douglas C. (committee member), Scott, Clayton D. (committee member), Balzano, Laura Kathryn (committee member).

Subjects/Keywords: Statistical image reconstruction for cardiac CT imaging; Regularization designs for isotropic and uniform spatial resolution or noise properties; Short-scan artifact removal using statistical weighting modification or additional prior regularization; Accelerating ordered-subsets (OS) method with double surrogate; Accelerating motion-compensated image reconstruction (MCIR) with variable splitting approach; Regularization designs using the hypothetical geometry; Biomedical Engineering; Electrical Engineering; Engineering (General); Engineering

…University of Michigan, MM&D c 2014 Google 3 nature of the X-ray source spectrum (ii)…

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APA (6^th Edition):

Cho, J. H. (2014). Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/110319

Chicago Manual of Style (16^th Edition):

Cho, Jang Hwan. “Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography.” 2014. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/110319.

MLA Handbook (7^th Edition):

Cho, Jang Hwan. “Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography.” 2014. Web. 20 Jan 2021.

Vancouver:

Cho JH. Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/110319.

Council of Science Editors:

Cho JH. Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/110319

22. Zhao, Feng. Methods for MRI RF Pulse Design and Image Reconstruction.

Degree: PhD, Biomedical Engineering, 2014, University of Michigan

URL: http://hdl.handle.net/2027.42/107071

► This thesis describes methods to improve magnetic resonance imaging (MRI) reconstruction and system calibration, namely, B1 field mapping which is to measure the spatial distribution… (more)

▼ This thesis describes methods to improve magnetic resonance imaging (MRI) reconstruction and system calibration, namely, B1 field mapping which is to measure the spatial distribution of the magnetic field produced by radiofrequency (RF) coils. We also developed methods of RF pulse design and steady-state imaging sequence design for applications such as fat suppression and magnetization transfer contrast imaging. There are five projects: (a) We developed a framework of iterative image reconstruction with separate magnitude and phase regularization where compressed sensing is used for the magnitude and special phase regularizers that are compatible with phase wrapping are designed for different applications. The proposed method significantly improves the phase image reconstruction while accelerates the data acquisition. (b) A modified Bloch-Siegert B1 mapping was developed to efficiently acquire both magnitude and phase of the B1 maps of multi-channel RF transmission systems. A regularized method was developed to jointly estimate the B1 magnitude and phase to reduce low signal-to-noise ratio regions. Furthermore, we developed a method for coil combination optimization for this multi-channel B1 mapping sequence based on Cramer-Rao lower bound analysis, to improve the raw data quality for B1 estimation. (c) We developed a four dimensional spectral-spatial fat saturation pulse that uniformly suppresses fat without exciting water in the presence of main magnetic field and B1 field inhomogeneity. At 3T, we showed that the proposed pulse can work more robustly than the standard spectrally selective fat saturation pulse with half the pulse length. (d) We applied the proposed fat saturation pulse to spoiled gradient echo sequence and small-tip fast recovery imaging sequence, with a modified RF spoiling scheme. We tested these proposed sequences on clinical applications like cartilage imaging and MR angiography and demonstrated their ability to simultaneously produce fat suppression and magnetization transfer contrast. We show that the proposed sequences can reduce the minimal repetition time and potentially lower the overall RF power deposition. (e) We designed a small tip fast recovery imaging sequence combined with a post-processing method to separate water from fat and remove banding artifacts simultaneously. Advisors/Committee Members: Fessler, Jeffrey A. (committee member), Noll, Douglas C. (committee member), Chenevert, Thomas L. (committee member), Nielsen, Jon-Fredrik (committee member).

Subjects/Keywords: Magnetic Resonance Imaging; Image Reconstruction; Phase Information Estimation; B1 Mapping; Fat Suppressed Imaging; Steady-state Imaging; Biomedical Engineering; Engineering

…x28;ﬁgures are from J-F Nielsen from The University of Michigan). (a) One…

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APA (6^th Edition):

Zhao, F. (2014). Methods for MRI RF Pulse Design and Image Reconstruction. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/107071

Chicago Manual of Style (16^th Edition):

Zhao, Feng. “Methods for MRI RF Pulse Design and Image Reconstruction.” 2014. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/107071.

MLA Handbook (7^th Edition):

Zhao, Feng. “Methods for MRI RF Pulse Design and Image Reconstruction.” 2014. Web. 20 Jan 2021.

Vancouver:

Zhao F. Methods for MRI RF Pulse Design and Image Reconstruction. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/107071.

Council of Science Editors:

Zhao F. Methods for MRI RF Pulse Design and Image Reconstruction. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/107071

23. Farjam, Reza. Computation Framework for Lesion Detection and Response Assessment Based Upon Physiological Imaging for Supporting Radiation Therapy of Brain Metastases.

Degree: PhD, Biomedical Engineering, 2013, University of Michigan

URL: http://hdl.handle.net/2027.42/97989

► Brain metastases are the most prevalent form of cancer in the central nervous system and up to 45% of cancer patients eventually develop brain metastases… (more)

▼ Brain metastases are the most prevalent form of cancer in the central nervous system and up to 45% of cancer patients eventually develop brain metastases during their illness. Selection of whole brain radiotherapy (WBRT) versus stereotactic radiosurgery, two routine treatments for brain metastases, highly depends on the number and size of metastatic lesions in a patient. Our clinical investigations reveal that up to 40% of brain metastases with a diameter <5mm could be missed in a routine clinical diagnosis using contrast-enhanced MRI. Hence, this dissertation initially describes the development of a template-matching based computer-aided detection (CAD) system for automatic detection of small lesions in post-Gd T1-weighted MRI to assist radiological diagnosis. Our results showed a significant improvement in detecting small lesions using the proposed methodology. When a cancer patient is given a treatment, it is very important to assess the tumor response to therapy early. This is traditionally performed by measuring a change in the gross tumor volume. However, changes in tumor physiology, which happen earlier than the volumetric changes, have the potential to provide a better means in prediction of tumor response to therapy and also could be used for therapy guidance. But, there are several challenges in assessment of tumor response to therapy, especially due to the heterogeneous distribution pattern of the physiological parameters in a tumor, image mis-registration issues caused by tumor shrinkage/increase across the time of followups, lack of methodologies combining information from different physiological viewpoints, and etc. Hence, this dissertation mainly focused on development of techniques overcoming these challenges using information from two important aspects of tumor physiology: tumor vascular and cellularity properties derived from dynamic contrast-enhance and diffusion-weighted MRI. Our proposed techniques were evaluated with lesions treated by either WBRT alone or combined with Bortezomib as a radiation sensitizer. We found that changes in both tumor vascular and cellularity properties play an important but different role for predicting tumor response to therapy, depending on the tumor types and underlying treatment. Also, we found that combing the two parameters provides a better tool for response assessment. Advisors/Committee Members: Cao, Yue (committee member), Noll, Douglas C. (committee member), Fowlkes, J. Brian (committee member), Hernandez, Luis (committee member).

Subjects/Keywords: Brain Metastases; Lesion Detection; Response Assessment; Biomedical Engineering; Engineering

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APA (6^th Edition):

Farjam, R. (2013). Computation Framework for Lesion Detection and Response Assessment Based Upon Physiological Imaging for Supporting Radiation Therapy of Brain Metastases. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/97989

Chicago Manual of Style (16^th Edition):

Farjam, Reza. “Computation Framework for Lesion Detection and Response Assessment Based Upon Physiological Imaging for Supporting Radiation Therapy of Brain Metastases.” 2013. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/97989.

MLA Handbook (7^th Edition):

Farjam, Reza. “Computation Framework for Lesion Detection and Response Assessment Based Upon Physiological Imaging for Supporting Radiation Therapy of Brain Metastases.” 2013. Web. 20 Jan 2021.

Vancouver:

Farjam R. Computation Framework for Lesion Detection and Response Assessment Based Upon Physiological Imaging for Supporting Radiation Therapy of Brain Metastases. [Internet] [Doctoral dissertation]. University of Michigan; 2013. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/97989.

Council of Science Editors:

Farjam R. Computation Framework for Lesion Detection and Response Assessment Based Upon Physiological Imaging for Supporting Radiation Therapy of Brain Metastases. [Doctoral Dissertation]. University of Michigan; 2013. Available from: http://hdl.handle.net/2027.42/97989

24. Sun, Hao. Topics in Steady-state MRI Sequences and RF Pulse Optimization.

Degree: PhD, Electrical Engineering: Systems, 2015, University of Michigan

URL: http://hdl.handle.net/2027.42/111514

► Small-tip fast recovery (STFR) is a recently proposed rapid steady-state magnetic resonance imaging (MRI) sequence that has the potential to be an alternative to the… (more)

▼ Small-tip fast recovery (STFR) is a recently proposed rapid steady-state magnetic resonance imaging (MRI) sequence that has the potential to be an alternative to the popular balanced steady-state free precession (bSSFP) imaging sequence, since they have similar signal level and tissue contrast, but STFR has reduced banding artifacts. In this dissertation, an analytic equation of the steady-state signal for the unspoiled version of STFR is first derived. It is shown that unspoiled-STFR is less sensitive to the inaccuracy in excitation than the previous proposed spoiled-STFR. By combining unspoiled-STFR with jointly designed tip-down and tip-up pulses, a 3D STFR acquisition over 3-4 cm thick 3D ROI with single coil and short RF pulses (1.7 ms) is demonstrated. Then, it is demonstrated that STFR can reliably detect functional MRI signal and the contrast is driven mainly from intra-voxel dephasing, not diffusion, using Monte Carlo simulation, human experiments and test-retest reliability. Following that another version of STFR using a spectral pre-winding pulse instead of the spatially tailored pulse is investigated, leading to less T2* weighting, easier implementation. Multidimensional selective RF pulse is a key part for STFR and many other MRI applications. Two novel RF pulse optimization methods are proposed. First, a minimax formulation that directly controls the maximum excitation error, and an effective optimization algorithm using variable splitting and alternating direction method of multipliers (ADMM). The proposed method reduced the maximum excitation by more than half in all the testing cases. Second, a method that jointly optimizes the excitation k-space trajectory and RF pulse is proposed. The k-space trajectory is parametrized using 2nd-order B-splines, and an interior point algorithm is used to explicitly solve the constrained optimization. An effective initialization method is also suggested. The joint design reduced the NRMSE by more than 30 percent compared to existing methods in inner volume excitation and pre-phasing problem. Using the proposed joint design, rapid inner volume STFR imaging with a 4 ms excitation pulse with single transmit coil is demonstrated. Finally, a regularized Bloch-Siegert B1 map reconstruction method is presented that significantly reduces the noise in estimated B1 maps. Advisors/Committee Members: Fessler, Jeffrey A. (committee member), Nielsen, Jon-Fredrik (committee member), Noll, Douglas C. (committee member), Balzano, Laura Kathryn (committee member).

Subjects/Keywords: MRI; pulse design; steady-state sequence; Electrical Engineering; Engineering

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APA (6^th Edition):

Sun, H. (2015). Topics in Steady-state MRI Sequences and RF Pulse Optimization. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/111514

Chicago Manual of Style (16^th Edition):

Sun, Hao. “Topics in Steady-state MRI Sequences and RF Pulse Optimization.” 2015. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/111514.

MLA Handbook (7^th Edition):

Sun, Hao. “Topics in Steady-state MRI Sequences and RF Pulse Optimization.” 2015. Web. 20 Jan 2021.

Vancouver:

Sun H. Topics in Steady-state MRI Sequences and RF Pulse Optimization. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/111514.

Council of Science Editors:

Sun H. Topics in Steady-state MRI Sequences and RF Pulse Optimization. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/111514

25. Allison, Michael J. Accelerated Computation of Regularized Estimates in Magnetic Resonance Imaging.

Degree: PhD, Electrical Engineering: Systems, 2014, University of Michigan

URL: http://hdl.handle.net/2027.42/107096

► Magnetic resonance imaging (MRI) is a non-invasive medical imaging modality that uses magnetic fields. Accurate estimates of these fields are often used to improve the… (more)

▼ Magnetic resonance imaging (MRI) is a non-invasive medical imaging modality that uses magnetic fields. Accurate estimates of these fields are often used to improve the quality of MR imaging techniques. Regularized estimators for such fields are robust and can provide high quality estimates but often at a significant computational cost. In this work, we investigate several of these estimators with a focus on developing novel minimization methods that reduce their computation times. First, we explore regularized receive coil sensitivity estimation by demonstrating the improved performance of regularized methods over existing, heuristic approaches and by presenting several algorithms, based on augmented Lagrangian methods, that minimize the quadratic cost function in half the time required by a preconditioned conjugate gradient (CG) method. Second, we present a general cost function that combines the regularized estimation of the main magnetic field inhomogeneity for both multiple echo time field map estimation and chemical shift based water-fat imaging. We present two methods, both based on optimization transfer principles, that reduce the computation time of this estimator by a factor of 30 compared to the existing separable quadratic surrogates method. We also evaluate the effectiveness of edge preserving regularization for field inhomogeneity estimation near tissue interfaces. Third, we present a novel alternating minimization method that uses augmented Lagrangian methods to accelerate the computation of the compressed sensing based water-fat image reconstruction problem by at least ten times compared to the existing nonlinear CG method. The algorithms presented in this thesis may also be applicable to other MRI topics including B1+ estimation, T1 estimation from variable flip angles, and R2* corrected or parallel imaging extensions of compressed sensing based water-fat imaging. Advisors/Committee Members: Fessler, Jeffrey A. (committee member), Noll, Douglas C. (committee member), Nielsen, Jon-Fredrik (committee member), Hero Iii, Alfred O. (committee member), Gilbert, Anna Catherine (committee member).

Subjects/Keywords: Magnetic Resonance Imaging; Medical Imaging; Optimization Methods; Regularized Estimation; Electrical Engineering; Engineering

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APA (6^th Edition):

Allison, M. J. (2014). Accelerated Computation of Regularized Estimates in Magnetic Resonance Imaging. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/107096

Chicago Manual of Style (16^th Edition):

Allison, Michael J. “Accelerated Computation of Regularized Estimates in Magnetic Resonance Imaging.” 2014. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/107096.

MLA Handbook (7^th Edition):

Allison, Michael J. “Accelerated Computation of Regularized Estimates in Magnetic Resonance Imaging.” 2014. Web. 20 Jan 2021.

Vancouver:

Allison MJ. Accelerated Computation of Regularized Estimates in Magnetic Resonance Imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/107096.

Council of Science Editors:

Allison MJ. Accelerated Computation of Regularized Estimates in Magnetic Resonance Imaging. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/107096

26. Yoon, Daehyun. Fast Joint Design of RF and Gradient Waveforms for MRI Parallel Excitation.

Degree: PhD, Electrical Engineering: Systems, 2012, University of Michigan

URL: http://hdl.handle.net/2027.42/96091

► For past few decades, magnetic resonance imaging (MRI) has been increasingly used for a wide variety of clinical and biological research due to its excellent… (more)

▼ For past few decades, magnetic resonance imaging (MRI) has been increasingly used for a wide variety of clinical and biological research due to its excellent contrast of soft tissues in high resolution. MRI is performed in roughly two sequential procedures: excitation and acquisition. In excitation, magnetization in the target imaging volume is prepared, and in acquisition, its Fourier transform samples are measured. Conventional excitation entails transmitting a magnetic field in a radio-frequency (RF) with a single RF transmission coil. While most RF transmission excite single slices, one shortcoming of the single coil RF transmission is that it is very hard to spatially tailor the RF pulse deposition pattern in 2D or 3D because there is just one source for the RF transmission. Unfortunately, this is a significant limitation for multi-dimensional excitation, which recently gained much interest as a potential solution for problems such as inner-volume imaging, signal recovery for functional MRI, and robust fat-saturation. Recently, parallel excitation, simultaneous transmission of multiple RF pulses with multiple transmission coils, has been proposed to overcome this limitation of conventional single coil transmission. Many RF pulse design methods have been proposed, but most of them focused only on the optimization of the RF pulse waveforms, leaving the gradient waveforms unoptimized. In this thesis, we introduce a fast joint optimization scheme for RF pulse and gradient waveforms in parallel excitation to further enhance the excitation accuracy in both small and large tip-angle domains. We assumed an RF pulse sequence for slice-selective excitation, which is composed of trains of weighted slice-selective basis RF pulses interleaved by in-plane gradient blips. Our algorithm seeks to find effective RF pulse weights and the in-plane gradient blips considering an off-resonance effect. We applied our algorithm in various application domains, and demonstrated its potential advantages over previous methods through computer simulations. Our algorithm could achieve higher excitation accuracy than previous methods due to more accurate modeling for off-resonance effects. Also our method could provide faster computation than conventional methods performing a convex optimization or an exhaustive greedy search by performing a fast greedy search in a much reduced candidate set. Advisors/Committee Members: Fessler, Jeffrey A. (committee member), Noll, Douglas C. (committee member), Chenevert, Thomas L. (committee member), Gilbert, Anna Catherine (committee member), Scott, Clayton D. (committee member).

Subjects/Keywords: Fast Joint Design of RF and Gradient Waveforms for MRI Parallel Excitation; Electrical Engineering; Engineering

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APA (6^th Edition):

Yoon, D. (2012). Fast Joint Design of RF and Gradient Waveforms for MRI Parallel Excitation. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/96091

Chicago Manual of Style (16^th Edition):

Yoon, Daehyun. “Fast Joint Design of RF and Gradient Waveforms for MRI Parallel Excitation.” 2012. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/96091.

MLA Handbook (7^th Edition):

Yoon, Daehyun. “Fast Joint Design of RF and Gradient Waveforms for MRI Parallel Excitation.” 2012. Web. 20 Jan 2021.

Vancouver:

Yoon D. Fast Joint Design of RF and Gradient Waveforms for MRI Parallel Excitation. [Internet] [Doctoral dissertation]. University of Michigan; 2012. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/96091.

Council of Science Editors:

Yoon D. Fast Joint Design of RF and Gradient Waveforms for MRI Parallel Excitation. [Doctoral Dissertation]. University of Michigan; 2012. Available from: http://hdl.handle.net/2027.42/96091

27. Koehler, Seth D. Auditory-Somatosensory Integration in Dorsal Cochlear Nucleus Mediates Normal and Phantom Sound Perception.

Degree: PhD, Biomedical Engineering, 2013, University of Michigan

URL: http://hdl.handle.net/2027.42/97934

► The dorsal cochlear nucleus (DCN) is the first auditory brainstem nucleus that processes and relays sensory information from multiple sensory modalities to higher auditory brain… (more)

▼ The dorsal cochlear nucleus (DCN) is the first auditory brainstem nucleus that processes and relays sensory information from multiple sensory modalities to higher auditory brain structures. Converging somatosensory and auditory inputs are integrated by bimodal DCN fusiform neurons, which use somatosensory context for improved auditory coding. Furthermore, phantom sound perception, or tinnitus, can be modulated or induced by somatosensory stimuli including facial pressure and has been linked to somatosensory-auditory processing in DCN. I present three in vivo neurophysiology studies in guinea pigs investigating the role of multisensory mechanisms in normal and tinnitus models. 1) DCN fusiform cells respond to sound with characteristic spike-timing patterns that are controlled by rapidly inactivating potassium conductances. I demonstrated here that somatosensory stimulation alters sound-evoked firing rates and temporal representations of sound for tens of milliseconds through synaptic modulation of intrinsic excitability. 2) Bimodal plasticity consists of alterations of sound-evoked responses for up to two hours after paired somatosensory-auditory stimulation. By varying the interval and order between sound and somatosensory stimuli, I demonstrated stimulus-timing dependent bimodal plasticity that implicates spike-timing dependent synaptic plasticity (STDP) as the underlying mechanism. The timing rules and time course of stimulus-timing dependent plasticity closely mimic those of STDP at synapses conveying somatosensory information to the DCN. These results suggest the DCN performs STDP-dependent adaptive processing such as suppression of body-generated sounds. 3) Finally, I assessed stimulus-timing dependence of bimodal plasticity in a tinnitus model. Guinea pigs were exposed to a narrowband noise that produced temporary shifts in auditory brainstem response thresholds and is known to produce tinnitus. Sixty percent of guinea pigs developed tinnitus according to behavioral testing by gap-induced prepulse inhibition of the acoustic startle response. Bimodal plasticity timing rules in animals with verified tinnitus were broader and more likely to be anti-Hebbian than those in sham animals or noise-exposed animals that did not develop tinnitus. Furthermore, exposed animals with tinnitus had weaker suppressive responses than either sham animals or exposed animals without tinnitus. These results suggest tinnitus development is linked to STDP, presenting a potential target for pharmacological or neuromodulatory tinnitus therapies. Advisors/Committee Members: Shore, Susan (committee member), Aldridge, J. Wayne (committee member), Zochowski, Michal R. (committee member), Wise, Kensall D. (committee member), Noll, Douglas C. (committee member).

Subjects/Keywords: Auditory System; Multisensory; Tinnitus; Plasticity; Spike-timing Dependent Plasticity; Dorsal Cochlear Nucleus; Biomedical Engineering; Physiology; Engineering; Science

…the University of Michigan Committee on the Use and Care of Animals (UCUCA)…

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APA (6^th Edition):

Koehler, S. D. (2013). Auditory-Somatosensory Integration in Dorsal Cochlear Nucleus Mediates Normal and Phantom Sound Perception. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/97934

Chicago Manual of Style (16^th Edition):

Koehler, Seth D. “Auditory-Somatosensory Integration in Dorsal Cochlear Nucleus Mediates Normal and Phantom Sound Perception.” 2013. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/97934.

MLA Handbook (7^th Edition):

Koehler, Seth D. “Auditory-Somatosensory Integration in Dorsal Cochlear Nucleus Mediates Normal and Phantom Sound Perception.” 2013. Web. 20 Jan 2021.

Vancouver:

Koehler SD. Auditory-Somatosensory Integration in Dorsal Cochlear Nucleus Mediates Normal and Phantom Sound Perception. [Internet] [Doctoral dissertation]. University of Michigan; 2013. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/97934.

Council of Science Editors:

Koehler SD. Auditory-Somatosensory Integration in Dorsal Cochlear Nucleus Mediates Normal and Phantom Sound Perception. [Doctoral Dissertation]. University of Michigan; 2013. Available from: http://hdl.handle.net/2027.42/97934

28. Shah, Yash Shailesh. Methods and Applications of Multivariate Pattern Analysis in Functional MRI Data Analysis.

Degree: PhD, Biomedical Engineering, 2015, University of Michigan

URL: http://hdl.handle.net/2027.42/111357

► In spite of the tremendous advances in science and technology, the human brain and its functions are still not completely understood. Functional magnetic resonance imaging… (more)

▼ In spite of the tremendous advances in science and technology, the human brain and its functions are still not completely understood. Functional magnetic resonance imaging (fMRI) is an imaging modality that allows for non-invasive study of brain function and physiology. Thus, fMRI has found many applications in various fields involved in the study of cognition, psychology, psychiatry, neuroscience, etc. Machine learning techniques have gained tremendous interest in recent times for fMRI data analysis. These methods involve learning from numerous examples and then making predictions for new unseen examples. This work addresses the use of machine learning techniques to find and study multivariate patterns in the fMRI brain data. The two main applications explored in this work include temporal brain-state prediction and subject categorization. The within-subject brain-state prediction setup has been used to compare and contrast three different acquisition techniques in a motor-visual activation study. It has also been implemented to highlight the differences in pain regulation networks in healthy controls and subjects with temporomandibular disorders. Lastly, regression has been used to predict graded fMRI activation on a continuous scale in a motor activation and craving study. The between-subject categorization setup has been used to distinguish between patients with Asperger's disorder and healthy controls. A major contribution of our work involves a novel multi-subject machine learning framework. This technique helps to learn a model which is based on information acquired from multiple other subjects' data in addition to the subject's own data. This has been used to classify the craving and non-craving brain states of nicotine-dependent subjects, allowing examination of both population-wide as well as subject-specific neural correlates of nicotine craving. A real-time neurofeedback setup was implemented to provide feedback to a subject using their own brain activation data. Subjects can then be trained to self-regulate their own brain activation. Advisors/Committee Members: Noll, Douglas C. (committee member), Peltier, Scott J. (committee member), Zubieta, Jon K. (committee member), Hernandez-Garcia, Luis (committee member), Syed, Zeeshan (committee member).

Subjects/Keywords: functional MRI data analysis; multivariate pattern analysis; machine learning; Biomedical Engineering; Engineering

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APA (6^th Edition):

Shah, Y. S. (2015). Methods and Applications of Multivariate Pattern Analysis in Functional MRI Data Analysis. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/111357

Chicago Manual of Style (16^th Edition):

Shah, Yash Shailesh. “Methods and Applications of Multivariate Pattern Analysis in Functional MRI Data Analysis.” 2015. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/111357.

MLA Handbook (7^th Edition):

Shah, Yash Shailesh. “Methods and Applications of Multivariate Pattern Analysis in Functional MRI Data Analysis.” 2015. Web. 20 Jan 2021.

Vancouver:

Shah YS. Methods and Applications of Multivariate Pattern Analysis in Functional MRI Data Analysis. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/111357.

Council of Science Editors:

Shah YS. Methods and Applications of Multivariate Pattern Analysis in Functional MRI Data Analysis. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/111357

29. Harrivel, Angela Rose. Monitoring Attentional State with Functional Near Infrared Spectroscopy.

Degree: PhD, Biomedical Engineering, 2014, University of Michigan

URL: http://hdl.handle.net/2027.42/108861

► Functional Near Infrared Spectroscopy (fNIRS) is a technique for quantifying hemodynamic activity in the brain. Its portability allows application in real world operational contexts. The… (more)

▼ Functional Near Infrared Spectroscopy (fNIRS) is a technique for quantifying hemodynamic activity in the brain. Its portability allows application in real world operational contexts. The ability to distinguish levels of task engagement in safety-critical situations is important for detecting and preventing attentional performance decrement. We therefore investigated whether fNIRS can be used to distinguish between high and low levels of task engagement during the performance of a selective attention task, and validated these results using functional magnetic resonance imaging (fMRI) as a gold standard. Participants performed the multi-source interference task (MSIT) while we recorded brain activity with fNIRS from two brain regions. One was a key region of the “task-positive” network, which is associated with relatively high levels of task engagement. The second was a key region of the “task-negative” network, which is associated with relatively low levels of task engagement (e.g., resting and not performing a task). Using activity in these regions as inputs to a multivariate pattern classifier, we were able to predict above chance levels whether participants were engaged in performing the MSIT or resting. Classifier input features were selected from an array of probe channels at each of the two locations based on the fit to a model of expected task activity, or on training data. Standard linear regression was implemented with both static and adaptive general linear models to remove concurrently measured physiological noise. Two types of models were used to process the fNIRS signals. One employed knowledge of the task being performed to determine the system’s best capability. The other did not, for a realistic characterization. We were also able to replicate prior findings from fMRI indicating that activity in “task-positive” and “task-negative” regions is negatively correlated during task performance. Finally, data from both companion and simultaneous fMRI experimental trials verified our assumptions about the sources of brain activity in the fNIRS experiment, established a upper bound on classification accuracy expectations for response to the MSIT, and served to validate our fNIRS classification results. Together, our findings suggest that fNIRS could prove quite useful for monitoring cognitive state in real-world settings. Advisors/Committee Members: Noll, Douglas C. (committee member), Peltier, Scott J. (committee member), Weissman, Daniel Howard (committee member), Hernandez-Garcia, Luis (committee member), Huppert, Theodore James (committee member).

Subjects/Keywords: Near Infra-red Spectroscopy; Default Mode Network; Classification; Attention; Biomedical Engineering; Engineering

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APA (6^th Edition):

Harrivel, A. R. (2014). Monitoring Attentional State with Functional Near Infrared Spectroscopy. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/108861

Chicago Manual of Style (16^th Edition):

Harrivel, Angela Rose. “Monitoring Attentional State with Functional Near Infrared Spectroscopy.” 2014. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/108861.

MLA Handbook (7^th Edition):

Harrivel, Angela Rose. “Monitoring Attentional State with Functional Near Infrared Spectroscopy.” 2014. Web. 20 Jan 2021.

Vancouver:

Harrivel AR. Monitoring Attentional State with Functional Near Infrared Spectroscopy. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/108861.

Council of Science Editors:

Harrivel AR. Monitoring Attentional State with Functional Near Infrared Spectroscopy. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/108861

30. Funai, Amanda K. Regularized Estimation of Main and RF Field Inhomogeneity and Longitudinal Relaxation Rate in Magnetic Resonance Imaging.

Degree: PhD, Electrical Engineering: Systems, 2011, University of Michigan

URL: http://hdl.handle.net/2027.42/86473

► In designing pulses and algorithms for magnetic resonance imaging, several simplifications to the Bloch equation are used. However, as magnetic resonance (MR) imaging requires higher… (more)

▼ In designing pulses and algorithms for magnetic resonance imaging, several simplifications to the Bloch equation are used. However, as magnetic resonance (MR) imaging requires higher temporal resolution and faster pulses are used, simplifications such as uniform main field (B0) strength and uniform radio-frequency (RF) transmit coil field (B1) strength no longer apply. Ignoring these non-uniformities can cause significant distortions. Accurate maps of the main and RF transmit coil field inhomogeneity are required for accurate pulse design and imaging. Standard estimation methods yield noisy maps, particularly in image regions having low spin density, and ignore other important factors, such as slice selection effects in B1 mapping and T2 effects in B0 mapping. This thesis uses more accurate signal models for the MR scans to derive iterative regularized estimators that show improvements over the conventional unregularized methods through Cramer-Rao Bound analysis, simulations, and real MR data. In fast MR imaging with long readout times, field inhomogeneity causes image distortion and blurring. This thesis first describes regularized methods for estimation of the off-resonance frequency at each voxel from two or more MR scans having different echo times, using algorithms that decrease monotonically a regularized least-squares cost function. A second challenge is that RF transmit coils produce non-uniform field strengths, so an excitation pulse will produce tip angles that vary substantially over the field of view. This thesis secondly describes a regularized method for B1 map estimation for each coil and for two or more tip angles. Using these scans and known slice profile, the iterative algorithm estimates both the magnitude and phase of each coil’s B1 map. To circumvent the challenge in conventional B1 mapping sequences of an long repetition time, this thesis thirdly describes a regularized method for joint B1 and T1 map estimation using a regularized method based on a penalized-likelihood cost function using the steady-state incoherent (SSI) imaging sequence with several scans with varying tip angles or repetition times. Advisors/Committee Members: Fessler, Jeffrey A. (committee member), Chenevert, Thomas L. (committee member), Gilbert, Anna Catherine (committee member), Noll, Douglas C. (committee member), Scott, Clayton D. (committee member).

Subjects/Keywords: Field Mapping; Magnetic Resonance Imaging; Penalized-likelihood Estimation; B1 Mapping; Electrical Engineering; Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Funai, A. K. (2011). Regularized Estimation of Main and RF Field Inhomogeneity and Longitudinal Relaxation Rate in Magnetic Resonance Imaging. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/86473

Chicago Manual of Style (16^th Edition):

Funai, Amanda K. “Regularized Estimation of Main and RF Field Inhomogeneity and Longitudinal Relaxation Rate in Magnetic Resonance Imaging.” 2011. Doctoral Dissertation, University of Michigan. Accessed January 20, 2021. http://hdl.handle.net/2027.42/86473.

MLA Handbook (7^th Edition):

Funai, Amanda K. “Regularized Estimation of Main and RF Field Inhomogeneity and Longitudinal Relaxation Rate in Magnetic Resonance Imaging.” 2011. Web. 20 Jan 2021.

Vancouver:

Funai AK. Regularized Estimation of Main and RF Field Inhomogeneity and Longitudinal Relaxation Rate in Magnetic Resonance Imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2011. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2027.42/86473.

Council of Science Editors:

Funai AK. Regularized Estimation of Main and RF Field Inhomogeneity and Longitudinal Relaxation Rate in Magnetic Resonance Imaging. [Doctoral Dissertation]. University of Michigan; 2011. Available from: http://hdl.handle.net/2027.42/86473

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Open Access Theses and Dissertations