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You searched for +publisher:"University of Michigan" +contributor:("Fessler, Jeffrey A."). Showing records 1 – 30 of 127 total matches.

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University of Michigan

1. Hamel, Michael. A Stochastic Imaging Technique for Spatio-Spectral Characterization of Special Nuclear Material.

Degree: PhD, Nuclear Engineering & Radiological Sciences, 2017, University of Michigan

 Radiation imaging is advantageous for detecting, locating and characterizing special nuclear material (SNM) in complex environments. A dual-particle imager (DPI) has been designed that is… (more)

Subjects/Keywords: radiation imaging; nuclear non-proliferation; neutron spectroscopy; stochastic image reconstruction; active interrogation; detection of special nuclear material; Nuclear Engineering and Radiological Sciences; Engineering

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APA (6th Edition):

Hamel, M. (2017). A Stochastic Imaging Technique for Spatio-Spectral Characterization of Special Nuclear Material. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/138693

Chicago Manual of Style (16th Edition):

Hamel, Michael. “A Stochastic Imaging Technique for Spatio-Spectral Characterization of Special Nuclear Material.” 2017. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/138693.

MLA Handbook (7th Edition):

Hamel, Michael. “A Stochastic Imaging Technique for Spatio-Spectral Characterization of Special Nuclear Material.” 2017. Web. 20 Sep 2020.

Vancouver:

Hamel M. A Stochastic Imaging Technique for Spatio-Spectral Characterization of Special Nuclear Material. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/138693.

Council of Science Editors:

Hamel M. A Stochastic Imaging Technique for Spatio-Spectral Characterization of Special Nuclear Material. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/138693


University of Michigan

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

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

 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)

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

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APA (6th 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 (16th Edition):

Sarkar, Saradwata. “Quantitative Assessment of Volume Change in Tumors Using Image Registration.” 2011. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/84652.

MLA Handbook (7th Edition):

Sarkar, Saradwata. “Quantitative Assessment of Volume Change in Tumors Using Image Registration.” 2011. Web. 20 Sep 2020.

Vancouver:

Sarkar S. Quantitative Assessment of Volume Change in Tumors Using Image Registration. [Internet] [Doctoral dissertation]. University of Michigan; 2011. [cited 2020 Sep 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

3. Shy, Daniel. Super-MeV Compton Imaging and 3D Gamma-Ray Imaging Using Pixelated CdZnTe.

Degree: PhD, Nuclear Science, 2020, University of Michigan

 The dissertation presents work in gamma-ray imaging in the MeV range, 3D Compton imaging, and time encoded imaging. The first thrust in high energy gamma-ray… (more)

Subjects/Keywords: Gamma-ray Imaging; 3D Gamma-ray Imaging; MeV Gamma rays; Nuclear Engineering and Radiological Sciences; Engineering

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APA (6th Edition):

Shy, D. (2020). Super-MeV Compton Imaging and 3D Gamma-Ray Imaging Using Pixelated CdZnTe. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/155099

Chicago Manual of Style (16th Edition):

Shy, Daniel. “Super-MeV Compton Imaging and 3D Gamma-Ray Imaging Using Pixelated CdZnTe.” 2020. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/155099.

MLA Handbook (7th Edition):

Shy, Daniel. “Super-MeV Compton Imaging and 3D Gamma-Ray Imaging Using Pixelated CdZnTe.” 2020. Web. 20 Sep 2020.

Vancouver:

Shy D. Super-MeV Compton Imaging and 3D Gamma-Ray Imaging Using Pixelated CdZnTe. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/155099.

Council of Science Editors:

Shy D. Super-MeV Compton Imaging and 3D Gamma-Ray Imaging Using Pixelated CdZnTe. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/155099


University of Michigan

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

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

 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 (6th 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 (16th Edition):

Huh, Won Seok. “Regularized Statistical Material Decomposition in Medical Imaging.” 2011. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/86549.

MLA Handbook (7th Edition):

Huh, Won Seok. “Regularized Statistical Material Decomposition in Medical Imaging.” 2011. Web. 20 Sep 2020.

Vancouver:

Huh WS. Regularized Statistical Material Decomposition in Medical Imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2011. [cited 2020 Sep 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

5. Moore, Brian. Robust Algorithms for Low-Rank and Sparse Matrix Models.

Degree: PhD, Electrical Engineering: Systems, 2018, University of Michigan

 Data in statistical signal processing problems is often inherently matrix-valued, and a natural first step in working with such data is to impose a model… (more)

Subjects/Keywords: machine learning; signal processing; optimization; statistics; robust algorithms; dictionary learning; Computer Science; Electrical Engineering; Engineering

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APA (6th Edition):

Moore, B. (2018). Robust Algorithms for Low-Rank and Sparse Matrix Models. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/143925

Chicago Manual of Style (16th Edition):

Moore, Brian. “Robust Algorithms for Low-Rank and Sparse Matrix Models.” 2018. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/143925.

MLA Handbook (7th Edition):

Moore, Brian. “Robust Algorithms for Low-Rank and Sparse Matrix Models.” 2018. Web. 20 Sep 2020.

Vancouver:

Moore B. Robust Algorithms for Low-Rank and Sparse Matrix Models. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/143925.

Council of Science Editors:

Moore B. Robust Algorithms for Low-Rank and Sparse Matrix Models. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/143925


University of Michigan

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

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

 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)

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

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APA (6th 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 (16th Edition):

Khalsa, Kimberly A. “Temporal Regularization Use in Dynamic Contrast-Enhanced MRI.” 2011. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/84566.

MLA Handbook (7th Edition):

Khalsa, Kimberly A. “Temporal Regularization Use in Dynamic Contrast-Enhanced MRI.” 2011. Web. 20 Sep 2020.

Vancouver:

Khalsa KA. Temporal Regularization Use in Dynamic Contrast-Enhanced MRI. [Internet] [Doctoral dissertation]. University of Michigan; 2011. [cited 2020 Sep 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

7. Bao, Yingze. Geometric and Semantic Scene Understanding.

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

 Estimating the 3D structure of a scene and recognizing scene elements are two kernel functions supporting many artificial intelligence applications. The ability to achieve these… (more)

Subjects/Keywords: Computer Vision; Object Detection; 3D Reconstruction; Structure from Motion; Layout Estimation; Computer Science; Engineering

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APA (6th Edition):

Bao, Y. (2014). Geometric and Semantic Scene Understanding. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/107131

Chicago Manual of Style (16th Edition):

Bao, Yingze. “Geometric and Semantic Scene Understanding.” 2014. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/107131.

MLA Handbook (7th Edition):

Bao, Yingze. “Geometric and Semantic Scene Understanding.” 2014. Web. 20 Sep 2020.

Vancouver:

Bao Y. Geometric and Semantic Scene Understanding. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/107131.

Council of Science Editors:

Bao Y. Geometric and Semantic Scene Understanding. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/107131


University of Michigan

8. Prasadan, Arvind. Learning, Inference, and Unmixing of Weak, Structured Signals in Noise.

Degree: PhD, Electrical Engineering: Systems, 2020, University of Michigan

 In this thesis, we study two methods that can be used to learn, infer, and unmix weak, structured signals in noise: the Dynamic Mode Decomposition… (more)

Subjects/Keywords: Dynamic Mode Decomposition; Blind Source Separation; Random Matrix Theory; Sparse Principal Component Analysis; Time Series Analysis; High Dimensional Statistics; Computer Science; Electrical Engineering; Mathematics; Statistics and Numeric Data; Engineering; Science

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APA (6th Edition):

Prasadan, A. (2020). Learning, Inference, and Unmixing of Weak, Structured Signals in Noise. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/155061

Chicago Manual of Style (16th Edition):

Prasadan, Arvind. “Learning, Inference, and Unmixing of Weak, Structured Signals in Noise.” 2020. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/155061.

MLA Handbook (7th Edition):

Prasadan, Arvind. “Learning, Inference, and Unmixing of Weak, Structured Signals in Noise.” 2020. Web. 20 Sep 2020.

Vancouver:

Prasadan A. Learning, Inference, and Unmixing of Weak, Structured Signals in Noise. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/155061.

Council of Science Editors:

Prasadan A. Learning, Inference, and Unmixing of Weak, Structured Signals in Noise. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/155061


University of Michigan

9. McGaffin, Madison G. X-ray CT Image Reconstruction on Highly-Parallel Architectures.

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

 Model-based image reconstruction (MBIR) methods for X-ray CT use accurate models of the CT acquisition process, the statistics of the noisy measurements, and noise-reducing regularization… (more)

Subjects/Keywords: Model-based image reconstruction; X-ray CT; Parallel computing; Electrical Engineering; Engineering

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APA (6th Edition):

McGaffin, M. G. (2015). X-ray CT Image Reconstruction on Highly-Parallel Architectures. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/113551

Chicago Manual of Style (16th Edition):

McGaffin, Madison G. “X-ray CT Image Reconstruction on Highly-Parallel Architectures.” 2015. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/113551.

MLA Handbook (7th Edition):

McGaffin, Madison G. “X-ray CT Image Reconstruction on Highly-Parallel Architectures.” 2015. Web. 20 Sep 2020.

Vancouver:

McGaffin MG. X-ray CT Image Reconstruction on Highly-Parallel Architectures. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/113551.

Council of Science Editors:

McGaffin MG. X-ray CT Image Reconstruction on Highly-Parallel Architectures. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/113551


University of Michigan

10. Rowland, David. Improving the Scope and Quality of Single-Molecule Data Analysis.

Degree: PhD, Biophysics, 2016, University of Michigan

 In this dissertation, I extend the scope and quality of the information that may be gained from a single-molecule imaging data set. First, I investigate… (more)

Subjects/Keywords: Single-molecule super-resolution microscopy analysis methods; Physics; Science

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APA (6th Edition):

Rowland, D. (2016). Improving the Scope and Quality of Single-Molecule Data Analysis. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/137112

Chicago Manual of Style (16th Edition):

Rowland, David. “Improving the Scope and Quality of Single-Molecule Data Analysis.” 2016. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/137112.

MLA Handbook (7th Edition):

Rowland, David. “Improving the Scope and Quality of Single-Molecule Data Analysis.” 2016. Web. 20 Sep 2020.

Vancouver:

Rowland D. Improving the Scope and Quality of Single-Molecule Data Analysis. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/137112.

Council of Science Editors:

Rowland D. Improving the Scope and Quality of Single-Molecule Data Analysis. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/137112


University of Michigan

11. Kim, Jung Kuk. Algorithm and Architecture Co-design for High-performance Digital Signal Processing.

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

 CMOS scaling has been the driving force behind the revolution of digital signal processing (DSP) systems, but scaling is slowing down and the CMOS device… (more)

Subjects/Keywords: algorithm and architecture co-design; digital signal processing; high-performance VLSI systems; spiking neural networks; X-ray computed tomography; machine learning; Electrical Engineering; Engineering

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APA (6th Edition):

Kim, J. K. (2015). Algorithm and Architecture Co-design for High-performance Digital Signal Processing. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/113344

Chicago Manual of Style (16th Edition):

Kim, Jung Kuk. “Algorithm and Architecture Co-design for High-performance Digital Signal Processing.” 2015. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/113344.

MLA Handbook (7th Edition):

Kim, Jung Kuk. “Algorithm and Architecture Co-design for High-performance Digital Signal Processing.” 2015. Web. 20 Sep 2020.

Vancouver:

Kim JK. Algorithm and Architecture Co-design for High-performance Digital Signal Processing. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/113344.

Council of Science Editors:

Kim JK. Algorithm and Architecture Co-design for High-performance Digital Signal Processing. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/113344


University of Michigan

12. Zheng, Jiabei. Improving Image Reconstruction for Digital Breast Tomosynthesis.

Degree: PhD, Electrical Engineering: Systems, 2017, University of Michigan

 Digital breast tomosynthesis (DBT) has been developed to reduce the issue of overlapping tissue in conventional 2-D mammography for breast cancer screening and diagnosis. In… (more)

Subjects/Keywords: digital breast tomosynthesis; tomographic reconstruction; iterative image reconstruction; image quality; computational modeling; Electrical Engineering; Engineering

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APA (6th Edition):

Zheng, J. (2017). Improving Image Reconstruction for Digital Breast Tomosynthesis. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/144059

Chicago Manual of Style (16th Edition):

Zheng, Jiabei. “Improving Image Reconstruction for Digital Breast Tomosynthesis.” 2017. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/144059.

MLA Handbook (7th Edition):

Zheng, Jiabei. “Improving Image Reconstruction for Digital Breast Tomosynthesis.” 2017. Web. 20 Sep 2020.

Vancouver:

Zheng J. Improving Image Reconstruction for Digital Breast Tomosynthesis. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/144059.

Council of Science Editors:

Zheng J. Improving Image Reconstruction for Digital Breast Tomosynthesis. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/144059


University of Michigan

13. Leblanc, Joel. Optical System Identification for Passive Electro-Optical Imaging.

Degree: PhD, Electrical Engineering: Systems, 2019, University of Michigan

 A statistical inverse-problem approach is presented for jointly estimating camera blur from aliased data of a known calibration target. Specifically, a parametric Maximum Likelihood (ML)… (more)

Subjects/Keywords: statistical inverse-problem approach to imaging; Electrical Engineering; Engineering

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APA (6th Edition):

Leblanc, J. (2019). Optical System Identification for Passive Electro-Optical Imaging. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/153395

Chicago Manual of Style (16th Edition):

Leblanc, Joel. “Optical System Identification for Passive Electro-Optical Imaging.” 2019. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/153395.

MLA Handbook (7th Edition):

Leblanc, Joel. “Optical System Identification for Passive Electro-Optical Imaging.” 2019. Web. 20 Sep 2020.

Vancouver:

Leblanc J. Optical System Identification for Passive Electro-Optical Imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/153395.

Council of Science Editors:

Leblanc J. Optical System Identification for Passive Electro-Optical Imaging. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/153395


University of Michigan

14. Rowland, David. Improving the Scope and Quality of Single-Molecule Data Analysis.

Degree: PhD, Biophysics, 2016, University of Michigan

 In this dissertation, I extend the scope and quality of the information that may be gained from a single-molecule imaging data set. First, I investigate… (more)

Subjects/Keywords: Single-molecule super-resolution microscopy analysis methods; Physics; Science

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APA (6th Edition):

Rowland, D. (2016). Improving the Scope and Quality of Single-Molecule Data Analysis. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/135862

Chicago Manual of Style (16th Edition):

Rowland, David. “Improving the Scope and Quality of Single-Molecule Data Analysis.” 2016. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/135862.

MLA Handbook (7th Edition):

Rowland, David. “Improving the Scope and Quality of Single-Molecule Data Analysis.” 2016. Web. 20 Sep 2020.

Vancouver:

Rowland D. Improving the Scope and Quality of Single-Molecule Data Analysis. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/135862.

Council of Science Editors:

Rowland D. Improving the Scope and Quality of Single-Molecule Data Analysis. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/135862


University of Michigan

15. Yoon, Seongjin. Electron Beam X-Ray Computed Tomography for Multiphase Flows and An Experimental Study of Inter-channel Mixing.

Degree: PhD, Naval Architecture & Marine Engineering, 2017, University of Michigan

 This thesis consists of two parts. In the first, a high speed X-ray Computed Tomography (CT) system for multiphase flows is developed. X-ray Computed Tomography… (more)

Subjects/Keywords: electron beam X-ray CT; statistical CT reconstruction; gap mixing; particle image velocimetry; singular value decomposition; Naval Architecture and Marine Engineering; Engineering

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APA (6th Edition):

Yoon, S. (2017). Electron Beam X-Ray Computed Tomography for Multiphase Flows and An Experimental Study of Inter-channel Mixing. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/138666

Chicago Manual of Style (16th Edition):

Yoon, Seongjin. “Electron Beam X-Ray Computed Tomography for Multiphase Flows and An Experimental Study of Inter-channel Mixing.” 2017. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/138666.

MLA Handbook (7th Edition):

Yoon, Seongjin. “Electron Beam X-Ray Computed Tomography for Multiphase Flows and An Experimental Study of Inter-channel Mixing.” 2017. Web. 20 Sep 2020.

Vancouver:

Yoon S. Electron Beam X-Ray Computed Tomography for Multiphase Flows and An Experimental Study of Inter-channel Mixing. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/138666.

Council of Science Editors:

Yoon S. Electron Beam X-Ray Computed Tomography for Multiphase Flows and An Experimental Study of Inter-channel Mixing. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/138666


University of Michigan

16. Lim, Hongki. Quantitative Image Reconstruction Methods for Low Signal-To-Noise Ratio Emission Tomography.

Degree: PhD, Electrical and Computer Engineering, 2020, University of Michigan

 Novel internal radionuclide therapies such as radioembolization (RE) with Y-90 loaded microspheres and targeted therapies labeled with Lu-177 offer a unique promise for personalized treatment… (more)

Subjects/Keywords: Medical imaging; Image reconstruction; Deep learning; Machine learning; Computer Science; Electrical Engineering; Radiology; Engineering; Health Sciences

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APA (6th Edition):

Lim, H. (2020). Quantitative Image Reconstruction Methods for Low Signal-To-Noise Ratio Emission Tomography. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/155171

Chicago Manual of Style (16th Edition):

Lim, Hongki. “Quantitative Image Reconstruction Methods for Low Signal-To-Noise Ratio Emission Tomography.” 2020. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/155171.

MLA Handbook (7th Edition):

Lim, Hongki. “Quantitative Image Reconstruction Methods for Low Signal-To-Noise Ratio Emission Tomography.” 2020. Web. 20 Sep 2020.

Vancouver:

Lim H. Quantitative Image Reconstruction Methods for Low Signal-To-Noise Ratio Emission Tomography. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/155171.

Council of Science Editors:

Lim H. Quantitative Image Reconstruction Methods for Low Signal-To-Noise Ratio Emission Tomography. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/155171


University of Michigan

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

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

 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)

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 (6th 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 (16th Edition):

Chu, Alan. “Simultaneous Multislice Functional Magnetic Resonance Imaging.” 2016. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/120669.

MLA Handbook (7th Edition):

Chu, Alan. “Simultaneous Multislice Functional Magnetic Resonance Imaging.” 2016. Web. 20 Sep 2020.

Vancouver:

Chu A. Simultaneous Multislice Functional Magnetic Resonance Imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2020 Sep 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


University of Michigan

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

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

 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)

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

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APA (6th 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 (16th Edition):

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

MLA Handbook (7th Edition):

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

Vancouver:

Cao A. Methods for Physiological Artifact Correction in Oscillating Steady State Imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2020 Sep 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

19. Zhai, Yuanhao. Perceptual Image Similarity Metrics and Applications.

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

 This dissertation presents research in perceptual image similarity metrics and applications, e.g., content-based image retrieval, perceptual image compression, image similarity assessment and texture analysis. The… (more)

Subjects/Keywords: Texture and image similarity metric; Texture and image retrieval; Texture and image classification; Perceptual image compression; Subjective experiment; Bilevel image similarity; Electrical Engineering; Engineering

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APA (6th Edition):

Zhai, Y. (2015). Perceptual Image Similarity Metrics and Applications. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/113586

Chicago Manual of Style (16th Edition):

Zhai, Yuanhao. “Perceptual Image Similarity Metrics and Applications.” 2015. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/113586.

MLA Handbook (7th Edition):

Zhai, Yuanhao. “Perceptual Image Similarity Metrics and Applications.” 2015. Web. 20 Sep 2020.

Vancouver:

Zhai Y. Perceptual Image Similarity Metrics and Applications. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/113586.

Council of Science Editors:

Zhai Y. Perceptual Image Similarity Metrics and Applications. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/113586


University of Michigan

20. Le, Mai. Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI.

Degree: PhD, Electrical Engineering: Systems, 2017, University of Michigan

 Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is a valuable diagnostic tool due to the combination of anatomical and physiological information it provides. However, the sequential… (more)

Subjects/Keywords: MRI reconstruction; Dynamic Contrast-Enhanced MRI; Variable Splitting Methods for Image Reconstruction; Electrical Engineering; Engineering

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APA (6th Edition):

Le, M. (2017). Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/138498

Chicago Manual of Style (16th Edition):

Le, Mai. “Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI.” 2017. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/138498.

MLA Handbook (7th Edition):

Le, Mai. “Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI.” 2017. Web. 20 Sep 2020.

Vancouver:

Le M. Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/138498.

Council of Science Editors:

Le M. Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/138498

21. Polack, John Kyle. A Maximum-Likelihood Approach for Localizing and Characterizing Special Nuclear Material with a Dual-Particle Imager.

Degree: PhD, Nuclear Engineering and Radiological Sciences, 2016, University of Michigan

 The threat of nuclear warfare is an ongoing global concern. The reduction of this threat is an international effort that is aided by numerous technologies… (more)

Subjects/Keywords: radiation imaging; spectrum unfolding; nuclear non-proliferation; nuclear safeguards; photon; neutron; Nuclear Engineering and Radiological Sciences; Engineering

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APA (6th Edition):

Polack, J. K. (2016). A Maximum-Likelihood Approach for Localizing and Characterizing Special Nuclear Material with a Dual-Particle Imager. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/133291

Chicago Manual of Style (16th Edition):

Polack, John Kyle. “A Maximum-Likelihood Approach for Localizing and Characterizing Special Nuclear Material with a Dual-Particle Imager.” 2016. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/133291.

MLA Handbook (7th Edition):

Polack, John Kyle. “A Maximum-Likelihood Approach for Localizing and Characterizing Special Nuclear Material with a Dual-Particle Imager.” 2016. Web. 20 Sep 2020.

Vancouver:

Polack JK. A Maximum-Likelihood Approach for Localizing and Characterizing Special Nuclear Material with a Dual-Particle Imager. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/133291.

Council of Science Editors:

Polack JK. A Maximum-Likelihood Approach for Localizing and Characterizing Special Nuclear Material with a Dual-Particle Imager. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/133291


University of Michigan

22. Jin, Curtis. New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media.

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

 Scattering hinders the passage of light through random media and consequently limits the usefulness of optical techniques for sensing and imaging. Thus, methods for increasing… (more)

Subjects/Keywords: Wave Propagation; Scattering; Random Matrix Theory; Numerical Methods; Iterative Methods; Statistical Signal Processing; Electrical Engineering; Engineering; Science

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APA (6th Edition):

Jin, C. (2014). New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/107051

Chicago Manual of Style (16th Edition):

Jin, Curtis. “New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media.” 2014. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/107051.

MLA Handbook (7th Edition):

Jin, Curtis. “New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media.” 2014. Web. 20 Sep 2020.

Vancouver:

Jin C. New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/107051.

Council of Science Editors:

Jin C. New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/107051


University of Michigan

23. Musheinesh, Malakeh. Model-Based Image Reconstruction For THz Imaging Systems.

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

 Broadband THz imaging is an emerging technology with a plethora of promising applications in biological imaging, nondestructive testing, security screening, and process control. Despite the… (more)

Subjects/Keywords: THz Technology; THz Image Reconstruction Methods; Electrical Engineering; Engineering

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APA (6th Edition):

Musheinesh, M. (2011). Model-Based Image Reconstruction For THz Imaging Systems. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/84496

Chicago Manual of Style (16th Edition):

Musheinesh, Malakeh. “Model-Based Image Reconstruction For THz Imaging Systems.” 2011. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/84496.

MLA Handbook (7th Edition):

Musheinesh, Malakeh. “Model-Based Image Reconstruction For THz Imaging Systems.” 2011. Web. 20 Sep 2020.

Vancouver:

Musheinesh M. Model-Based Image Reconstruction For THz Imaging Systems. [Internet] [Doctoral dissertation]. University of Michigan; 2011. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/84496.

Council of Science Editors:

Musheinesh M. Model-Based Image Reconstruction For THz Imaging Systems. [Doctoral Dissertation]. University of Michigan; 2011. Available from: http://hdl.handle.net/2027.42/84496


University of Michigan

24. Hong, David. Learning Low-Dimensional Models for Heterogeneous Data.

Degree: PhD, Electrical Engineering: Systems, 2019, University of Michigan

 Modern data analysis increasingly involves extracting insights, trends and patterns from large and messy data collected from myriad heterogeneous sources. The scale and heterogeneity present… (more)

Subjects/Keywords: low-dimensional models; heterogeneous data; random matrix theory; principal component analysis; tensor decomposition; unions of subspaces; Computer Science; Electrical Engineering; Engineering

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APA (6th Edition):

Hong, D. (2019). Learning Low-Dimensional Models for Heterogeneous Data. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/150043

Chicago Manual of Style (16th Edition):

Hong, David. “Learning Low-Dimensional Models for Heterogeneous Data.” 2019. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/150043.

MLA Handbook (7th Edition):

Hong, David. “Learning Low-Dimensional Models for Heterogeneous Data.” 2019. Web. 20 Sep 2020.

Vancouver:

Hong D. Learning Low-Dimensional Models for Heterogeneous Data. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/150043.

Council of Science Editors:

Hong D. Learning Low-Dimensional Models for Heterogeneous Data. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/150043


University of Michigan

25. Lee, Gyemin. Machine Learning for Flow Cytometry Data Analysis.

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

 This thesis concerns the problem of automatic flow cytometry data analysis. Flow cytometry is a technique for rapid cell analysis and widely used in many… (more)

Subjects/Keywords: Machine Learning; Flow Cytometry; Support Vector Machine; Mixture Models; EM Algorithms; Statistical File Matching; Electrical Engineering; Engineering

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APA (6th Edition):

Lee, G. (2011). Machine Learning for Flow Cytometry Data Analysis. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/89818

Chicago Manual of Style (16th Edition):

Lee, Gyemin. “Machine Learning for Flow Cytometry Data Analysis.” 2011. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/89818.

MLA Handbook (7th Edition):

Lee, Gyemin. “Machine Learning for Flow Cytometry Data Analysis.” 2011. Web. 20 Sep 2020.

Vancouver:

Lee G. Machine Learning for Flow Cytometry Data Analysis. [Internet] [Doctoral dissertation]. University of Michigan; 2011. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/89818.

Council of Science Editors:

Lee G. Machine Learning for Flow Cytometry Data Analysis. [Doctoral Dissertation]. University of Michigan; 2011. Available from: http://hdl.handle.net/2027.42/89818


University of Michigan

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

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

 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)

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

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APA (6th 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 (16th Edition):

Williams, Sydney. “Constrained and Spectral-Spatial RF Pulse Design for Magnetic Resonance Imaging.” 2018. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/147647.

MLA Handbook (7th Edition):

Williams, Sydney. “Constrained and Spectral-Spatial RF Pulse Design for Magnetic Resonance Imaging.” 2018. Web. 20 Sep 2020.

Vancouver:

Williams S. Constrained and Spectral-Spatial RF Pulse Design for Magnetic Resonance Imaging. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2020 Sep 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

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

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

 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)

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

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APA (6th 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 (16th Edition):

Cha, Kenny. “Computer-Aided Image Analysis and Decision Support System for Bladder Cancer.” 2017. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/140968.

MLA Handbook (7th Edition):

Cha, Kenny. “Computer-Aided Image Analysis and Decision Support System for Bladder Cancer.” 2017. Web. 20 Sep 2020.

Vancouver:

Cha K. Computer-Aided Image Analysis and Decision Support System for Bladder Cancer. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2020 Sep 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

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

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

 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 (6th 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 (16th Edition):

Muckley, Matthew J. “Acceleration Methods for MRI.” 2016. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/120841.

MLA Handbook (7th Edition):

Muckley, Matthew J. “Acceleration Methods for MRI.” 2016. Web. 20 Sep 2020.

Vancouver:

Muckley MJ. Acceleration Methods for MRI. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2020 Sep 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

29. Long, Yong. Statistical Image Reconstruction and Motion Estimation for Image-Guided Radiotherapy.

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

 Image reconstruction and motion estimation are very important for image-guided radiotherapy (IGRT). Three-dimensional reconstruction of patient anatomy using X-ray computed tomography (CT) allows identification of… (more)

Subjects/Keywords: X-Ray CT; Statistical Image Reconstruction; Image-Guided Radiotherapy; Image Registration; Forward and Back-projection; Dual-Energy CT; Electrical Engineering; Engineering

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APA (6th Edition):

Long, Y. (2011). Statistical Image Reconstruction and Motion Estimation for Image-Guided Radiotherapy. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/86254

Chicago Manual of Style (16th Edition):

Long, Yong. “Statistical Image Reconstruction and Motion Estimation for Image-Guided Radiotherapy.” 2011. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/86254.

MLA Handbook (7th Edition):

Long, Yong. “Statistical Image Reconstruction and Motion Estimation for Image-Guided Radiotherapy.” 2011. Web. 20 Sep 2020.

Vancouver:

Long Y. Statistical Image Reconstruction and Motion Estimation for Image-Guided Radiotherapy. [Internet] [Doctoral dissertation]. University of Michigan; 2011. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/86254.

Council of Science Editors:

Long Y. Statistical Image Reconstruction and Motion Estimation for Image-Guided Radiotherapy. [Doctoral Dissertation]. University of Michigan; 2011. Available from: http://hdl.handle.net/2027.42/86254


University of Michigan

30. Prelee, Matthew A. Manhattan Cutset Sampling and Sensor Networks.

Degree: PhD, Electrical Engineering: Systems, 2016, University of Michigan

 Cutset sampling is a new approach to acquiring two-dimensional data, i.e., images, where values are recorded densely along straight lines. This type of sampling is… (more)

Subjects/Keywords: image sampling; sensor networks; Electrical Engineering; Engineering

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APA (6th Edition):

Prelee, M. A. (2016). Manhattan Cutset Sampling and Sensor Networks. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/120876

Chicago Manual of Style (16th Edition):

Prelee, Matthew A. “Manhattan Cutset Sampling and Sensor Networks.” 2016. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/120876.

MLA Handbook (7th Edition):

Prelee, Matthew A. “Manhattan Cutset Sampling and Sensor Networks.” 2016. Web. 20 Sep 2020.

Vancouver:

Prelee MA. Manhattan Cutset Sampling and Sensor Networks. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/120876.

Council of Science Editors:

Prelee MA. Manhattan Cutset Sampling and Sensor Networks. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/120876

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