subject:(Image registration)

Rice University

1. Vargas, Arturo. Radial MILO: A 4D Image Registration Algorithm Based on Filtering Block Match Data via l1-minimization.

Degree: MA, Engineering, 2015, Rice University

URL: http://hdl.handle.net/1911/87690

► Minimal l1 Perturbation to Block Match Data (MILO) is a spatially accurate image registration algorithm developed for thoracic CT inhale/exhale images. The MILO algorithm consists… (more)

Subjects/Keywords: Image Registration

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APA (6^th Edition):

Vargas, A. (2015). Radial MILO: A 4D Image Registration Algorithm Based on Filtering Block Match Data via l1-minimization. (Masters Thesis). Rice University. Retrieved from http://hdl.handle.net/1911/87690

Chicago Manual of Style (16^th Edition):

Vargas, Arturo. “Radial MILO: A 4D Image Registration Algorithm Based on Filtering Block Match Data via l1-minimization.” 2015. Masters Thesis, Rice University. Accessed February 27, 2021. http://hdl.handle.net/1911/87690.

MLA Handbook (7^th Edition):

Vargas, Arturo. “Radial MILO: A 4D Image Registration Algorithm Based on Filtering Block Match Data via l1-minimization.” 2015. Web. 27 Feb 2021.

Vancouver:

Vargas A. Radial MILO: A 4D Image Registration Algorithm Based on Filtering Block Match Data via l1-minimization. [Internet] [Masters thesis]. Rice University; 2015. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/1911/87690.

Council of Science Editors:

Vargas A. Radial MILO: A 4D Image Registration Algorithm Based on Filtering Block Match Data via l1-minimization. [Masters Thesis]. Rice University; 2015. Available from: http://hdl.handle.net/1911/87690

University of North Texas

2. Duraisamy, Prakash. 3D Reconstruction Using Lidar and Visual Images.

Degree: 2012, University of North Texas

URL: https://digital.library.unt.edu/ark:/67531/metadc177193/

► In this research, multi-perspective image registration using LiDAR and visual images was considered. 2D-3D image registration is a difficult task because it requires the extraction… (more)

Subjects/Keywords: LiDar; registration; image

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APA (6^th Edition):

Duraisamy, P. (2012). 3D Reconstruction Using Lidar and Visual Images. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc177193/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Duraisamy, Prakash. “3D Reconstruction Using Lidar and Visual Images.” 2012. Thesis, University of North Texas. Accessed February 27, 2021. https://digital.library.unt.edu/ark:/67531/metadc177193/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Duraisamy, Prakash. “3D Reconstruction Using Lidar and Visual Images.” 2012. Web. 27 Feb 2021.

Vancouver:

Duraisamy P. 3D Reconstruction Using Lidar and Visual Images. [Internet] [Thesis]. University of North Texas; 2012. [cited 2021 Feb 27]. Available from: https://digital.library.unt.edu/ark:/67531/metadc177193/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Duraisamy P. 3D Reconstruction Using Lidar and Visual Images. [Thesis]. University of North Texas; 2012. Available from: https://digital.library.unt.edu/ark:/67531/metadc177193/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

3. Zang, Xiaonan. Ebus/ct Fusion for Image-guided Bronchoscopy.

Degree: 2016, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/28651

► Many technical innovations in multimodal radiologic imaging and bronchoscopy have arisen to improve lung-cancer staging techniques. Among the innovations, endobronchial ultrasound (EBUS), which provides live… (more)

Subjects/Keywords: image segmentation; image registration; ultrasound

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APA (6^th Edition):

Zang, X. (2016). Ebus/ct Fusion for Image-guided Bronchoscopy. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/28651

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Zang, Xiaonan. “Ebus/ct Fusion for Image-guided Bronchoscopy.” 2016. Thesis, Penn State University. Accessed February 27, 2021. https://submit-etda.libraries.psu.edu/catalog/28651.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Zang, Xiaonan. “Ebus/ct Fusion for Image-guided Bronchoscopy.” 2016. Web. 27 Feb 2021.

Vancouver:

Zang X. Ebus/ct Fusion for Image-guided Bronchoscopy. [Internet] [Thesis]. Penn State University; 2016. [cited 2021 Feb 27]. Available from: https://submit-etda.libraries.psu.edu/catalog/28651.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zang X. Ebus/ct Fusion for Image-guided Bronchoscopy. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/28651

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

4. Rekha, S. (author). Optical Coherence Tomography - Histology Registration: An automated framework towards facilitation of intra-operative pathology.

Degree: 2016, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:496074f9-ebfa-4760-92a3-3bdd522279b4

►

Registration between histology and ex-vivo Full Field Optical Coherence Tomography (FF-OCT) can help in many clinical applications including identifying surgical margin in a tumour tissue… (more)

Subjects/Keywords: Medical Image Processing; Image Registration

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APA (6^th Edition):

Rekha, S. (. (2016). Optical Coherence Tomography - Histology Registration: An automated framework towards facilitation of intra-operative pathology. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:496074f9-ebfa-4760-92a3-3bdd522279b4

Chicago Manual of Style (16^th Edition):

Rekha, S (author). “Optical Coherence Tomography - Histology Registration: An automated framework towards facilitation of intra-operative pathology.” 2016. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:496074f9-ebfa-4760-92a3-3bdd522279b4.

MLA Handbook (7^th Edition):

Rekha, S (author). “Optical Coherence Tomography - Histology Registration: An automated framework towards facilitation of intra-operative pathology.” 2016. Web. 27 Feb 2021.

Vancouver:

Rekha S(. Optical Coherence Tomography - Histology Registration: An automated framework towards facilitation of intra-operative pathology. [Internet] [Masters thesis]. Delft University of Technology; 2016. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:496074f9-ebfa-4760-92a3-3bdd522279b4.

Council of Science Editors:

Rekha S(. Optical Coherence Tomography - Histology Registration: An automated framework towards facilitation of intra-operative pathology. [Masters Thesis]. Delft University of Technology; 2016. Available from: http://resolver.tudelft.nl/uuid:496074f9-ebfa-4760-92a3-3bdd522279b4

NSYSU

5. Tseng, Jen-ping. A Study of Feature Matching Approaches for Registration of Remote Sensing Imageries at Various Times from Different Sources.

Degree: Master, Marine Environment and Engineering, 2010, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1022110-093813

► Image Registration plays a very important role in the field of remote sensing. In order to have a better registration quality and make the automatization… (more)

▼ Image Registration plays a very important role in the field of remote sensing. In order to have a better registration quality and make the automatization possible, choos ing and matching the control points from conjugate images become very important. In fact, the control points required for image registration should have following three key factors, that is, the amount, validity and distribution of control points. ããIn the study, we take QuickBird Satellite Images as the main ones; on the other hand, it conducts two groups of image registrations resulted from aerial images at various times. After detecting feature points using different algorithms, the study makes use of feature matching methods to get conjugate points between two overlapped images. The algorithms used above are SIFT, ASIFT and MESR. SIFT is an algorithm which invariant to scales, rotation, affine stretch and change in brightness. ASIFT undertakes simulations based on the theory of SIFT and thus carries out fully affine invariant. The feature points obtained from MSER have physical meaning in its location. By using feature matching algorithms like K-d tree and BBF, the matched feature points from two overlapped images would be turned into the conjugate points which can be control points for image registration. ããDuring the process of image preprocessing, it is learned that the feature points detected by SIFT and MSER through feature matching are very few. Hence, this study attempts to employ histogram specificationãcontrast stretching and scale change methods to see if it is helpful to the feature detections and matching through change of image quality and image size. The experiment found that scale change will improve both the amount and accuracy of conjugate points detected by different algorithms. When considering distribution of the feature points, the study takes advantage of image cropping approach to conduct feature detections and matching individually. It is found that more conjugate points with uniform distribution can be obtained via image cropping technique. Advisors/Committee Members: Ming-Jer Huang (chair), Tien-Yuan Shih (chair), Yi-Hsin Tseng (chair), Liang-Hui Lee (chair), Shiahn-Wern Shyue (committee member).

Subjects/Keywords: SIFT; ASIFT; MSER; Image registration

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APA (6^th Edition):

Tseng, J. (2010). A Study of Feature Matching Approaches for Registration of Remote Sensing Imageries at Various Times from Different Sources. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1022110-093813

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Tseng, Jen-ping. “A Study of Feature Matching Approaches for Registration of Remote Sensing Imageries at Various Times from Different Sources.” 2010. Thesis, NSYSU. Accessed February 27, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1022110-093813.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Tseng, Jen-ping. “A Study of Feature Matching Approaches for Registration of Remote Sensing Imageries at Various Times from Different Sources.” 2010. Web. 27 Feb 2021.

Vancouver:

Tseng J. A Study of Feature Matching Approaches for Registration of Remote Sensing Imageries at Various Times from Different Sources. [Internet] [Thesis]. NSYSU; 2010. [cited 2021 Feb 27]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1022110-093813.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tseng J. A Study of Feature Matching Approaches for Registration of Remote Sensing Imageries at Various Times from Different Sources. [Thesis]. NSYSU; 2010. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1022110-093813

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Queens University

6. Eveleigh, Ryan. MRI Registration for Human Hip Kinematics .

Degree: Mechanical and Materials Engineering, 2016, Queens University

URL: http://hdl.handle.net/1974/14634

► Measurement of joint kinematics can provide knowledge to help improve joint prosthesis design, as well as identify joint motion patterns that may lead to joint… (more)

Subjects/Keywords: Hip Kinematics ; Image Registration ; MRI

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APA (6^th Edition):

Eveleigh, R. (2016). MRI Registration for Human Hip Kinematics . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/14634

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Eveleigh, Ryan. “MRI Registration for Human Hip Kinematics .” 2016. Thesis, Queens University. Accessed February 27, 2021. http://hdl.handle.net/1974/14634.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Eveleigh, Ryan. “MRI Registration for Human Hip Kinematics .” 2016. Web. 27 Feb 2021.

Vancouver:

Eveleigh R. MRI Registration for Human Hip Kinematics . [Internet] [Thesis]. Queens University; 2016. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/1974/14634.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Eveleigh R. MRI Registration for Human Hip Kinematics . [Thesis]. Queens University; 2016. Available from: http://hdl.handle.net/1974/14634

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Oregon State University

7. Liu, Tian. Region based image matching for 3D object recognition.

Degree: MS, Computer Science, 2010, Oregon State University

URL: http://hdl.handle.net/1957/16869

► 3D object recognition is a very difficult and important problem in computer vision, arising in a wide range of applications. Typically in 3D object recognition,… (more)

Subjects/Keywords: object recognition; Image registration

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APA (6^th Edition):

Liu, T. (2010). Region based image matching for 3D object recognition. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/16869

Chicago Manual of Style (16^th Edition):

Liu, Tian. “Region based image matching for 3D object recognition.” 2010. Masters Thesis, Oregon State University. Accessed February 27, 2021. http://hdl.handle.net/1957/16869.

MLA Handbook (7^th Edition):

Liu, Tian. “Region based image matching for 3D object recognition.” 2010. Web. 27 Feb 2021.

Vancouver:

Liu T. Region based image matching for 3D object recognition. [Internet] [Masters thesis]. Oregon State University; 2010. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/1957/16869.

Council of Science Editors:

Liu T. Region based image matching for 3D object recognition. [Masters Thesis]. Oregon State University; 2010. Available from: http://hdl.handle.net/1957/16869

University of Illinois – Chicago

8. Caldwell, Brandon M. Correlating Histopathology and Radiologic Imaging to Validate Prostate Cancer Detection.

Degree: 2018, University of Illinois – Chicago

URL: http://hdl.handle.net/10027/22664

► Radiologic imaging is entrenched in standard practice for screening men with suspicion of prostate cancer (PCa) and to inform treatment decisions. Correlating in-vivo imaging to… (more)

▼ Radiologic imaging is entrenched in standard practice for screening men with suspicion of prostate cancer (PCa) and to inform treatment decisions. Correlating in-vivo imaging to the radical prostatectomy (RP) specimen, however, is a challenging task due to the vast differences in resolution, scale, and deformation of the tissue. Microscopic examination of the RP specimen represents the gold-standard for diagnosis of PCa, so correlation with radiologic imaging is necessary in order to validate PCa detection competency. In this work, a methodology and program are presented with three aims: one, match histopathology slices to their corresponding radiologic images; two, register histopathology images to their corresponding radiologic image; and three, validate PCa detection in the radiologic image based on the registration with histopathology. Diffusion weighted imaging (DWI) (b50-b2000) was used in this work for proof of concept. Histopathology slides were scanned and processed in order to be compatible with a novel registration program. A slice matching method was established and a program, process_H, was created in MatLab (v2017b. Natick, MA) in order to register reconstructed histopathology slices to their closest corresponding DWI slice. A cohort of three RP patients, 29 total histopathological slices, with pre-operative multi-parametric magnetic resonance images (mpMRIs) was identified. Using this cohort, a set of histological images was prepared and process_H registered the respective images, creating validation sets for the registration as well as binary pixel-by-pixel data sets defining PCa by Gleason Score (GS). These pixel-by-pixel data sets were then used to validate PCa detection from the in-vivo DWIs by means of receiver operating characteristic (ROC) curves. This work specifically compares the diffusion coefficient (D), distributed diffusion coefficient (DDC), and a heterogeneity index (α) to GS. Our results show utility for our methodology and program in the validation of PCa. Further development will make this tool a valuable addition for validating new imaging sequences and those in current use. Advisors/Committee Members: Magin, Richard (advisor), Abern, Michael R. (committee member), Luciano, Cristian (committee member), Magin, Richard (chair).

Subjects/Keywords: prostate cancer; image registration; MRI

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APA (6^th Edition):

Caldwell, B. M. (2018). Correlating Histopathology and Radiologic Imaging to Validate Prostate Cancer Detection. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/22664

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Caldwell, Brandon M. “Correlating Histopathology and Radiologic Imaging to Validate Prostate Cancer Detection.” 2018. Thesis, University of Illinois – Chicago. Accessed February 27, 2021. http://hdl.handle.net/10027/22664.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Caldwell, Brandon M. “Correlating Histopathology and Radiologic Imaging to Validate Prostate Cancer Detection.” 2018. Web. 27 Feb 2021.

Vancouver:

Caldwell BM. Correlating Histopathology and Radiologic Imaging to Validate Prostate Cancer Detection. [Internet] [Thesis]. University of Illinois – Chicago; 2018. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/10027/22664.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Caldwell BM. Correlating Histopathology and Radiologic Imaging to Validate Prostate Cancer Detection. [Thesis]. University of Illinois – Chicago; 2018. Available from: http://hdl.handle.net/10027/22664

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Hong Kong University of Science and Technology

9. So, Wai King. Learning-based dissimilarity measure for rigid and non-rigid medical image registration.

Degree: 2017, Hong Kong University of Science and Technology

URL: http://repository.ust.hk/ir/Record/1783.1-87953 ; https://doi.org/10.14711/thesis-b1778942 ; http://repository.ust.hk/ir/bitstream/1783.1-87953/1/th_redirect.html

► Image registration is widely used in different areas. It plays an important role in medical image analysis, group analysis and statistical parametric mapping. For the… (more)

Subjects/Keywords: Image registration ; Analysis ; Diagnostic imaging

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APA (6^th Edition):

So, W. K. (2017). Learning-based dissimilarity measure for rigid and non-rigid medical image registration. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-87953 ; https://doi.org/10.14711/thesis-b1778942 ; http://repository.ust.hk/ir/bitstream/1783.1-87953/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

So, Wai King. “Learning-based dissimilarity measure for rigid and non-rigid medical image registration.” 2017. Thesis, Hong Kong University of Science and Technology. Accessed February 27, 2021. http://repository.ust.hk/ir/Record/1783.1-87953 ; https://doi.org/10.14711/thesis-b1778942 ; http://repository.ust.hk/ir/bitstream/1783.1-87953/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

So, Wai King. “Learning-based dissimilarity measure for rigid and non-rigid medical image registration.” 2017. Web. 27 Feb 2021.

Vancouver:

So WK. Learning-based dissimilarity measure for rigid and non-rigid medical image registration. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2017. [cited 2021 Feb 27]. Available from: http://repository.ust.hk/ir/Record/1783.1-87953 ; https://doi.org/10.14711/thesis-b1778942 ; http://repository.ust.hk/ir/bitstream/1783.1-87953/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

So WK. Learning-based dissimilarity measure for rigid and non-rigid medical image registration. [Thesis]. Hong Kong University of Science and Technology; 2017. Available from: http://repository.ust.hk/ir/Record/1783.1-87953 ; https://doi.org/10.14711/thesis-b1778942 ; http://repository.ust.hk/ir/bitstream/1783.1-87953/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

10. Cao, Y. (author). A tailored fMRI image processing pipeline based on ITK.

Degree: 2016, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:a4c07b84-24ed-417a-9ad7-779bdd2422f0

►

In neuroscience research, fMRI image analysis is a major approach to identify the relationships between brain region and behavior. fMRI provides delayed real time brain… (more)

Subjects/Keywords: fMRI; Image registration; GLM; FDR

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APA (6^th Edition):

Cao, Y. (. (2016). A tailored fMRI image processing pipeline based on ITK. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:a4c07b84-24ed-417a-9ad7-779bdd2422f0

Chicago Manual of Style (16^th Edition):

Cao, Y (author). “A tailored fMRI image processing pipeline based on ITK.” 2016. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:a4c07b84-24ed-417a-9ad7-779bdd2422f0.

MLA Handbook (7^th Edition):

Cao, Y (author). “A tailored fMRI image processing pipeline based on ITK.” 2016. Web. 27 Feb 2021.

Vancouver:

Cao Y(. A tailored fMRI image processing pipeline based on ITK. [Internet] [Masters thesis]. Delft University of Technology; 2016. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:a4c07b84-24ed-417a-9ad7-779bdd2422f0.

Council of Science Editors:

Cao Y(. A tailored fMRI image processing pipeline based on ITK. [Masters Thesis]. Delft University of Technology; 2016. Available from: http://resolver.tudelft.nl/uuid:a4c07b84-24ed-417a-9ad7-779bdd2422f0

11. SUN YIN. Fast registration of contrast-enhanced magnetic resonance images of the breast.

Degree: 2007, National University of Singapore

URL: http://scholarbank.nus.edu.sg/handle/10635/13046

Subjects/Keywords: Image registration

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APA (6^th Edition):

YIN, S. (2007). Fast registration of contrast-enhanced magnetic resonance images of the breast. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/13046

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

YIN, SUN. “Fast registration of contrast-enhanced magnetic resonance images of the breast.” 2007. Thesis, National University of Singapore. Accessed February 27, 2021. http://scholarbank.nus.edu.sg/handle/10635/13046.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

YIN, SUN. “Fast registration of contrast-enhanced magnetic resonance images of the breast.” 2007. Web. 27 Feb 2021.

Vancouver:

YIN S. Fast registration of contrast-enhanced magnetic resonance images of the breast. [Internet] [Thesis]. National University of Singapore; 2007. [cited 2021 Feb 27]. Available from: http://scholarbank.nus.edu.sg/handle/10635/13046.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

YIN S. Fast registration of contrast-enhanced magnetic resonance images of the breast. [Thesis]. National University of Singapore; 2007. Available from: http://scholarbank.nus.edu.sg/handle/10635/13046

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Drexel University

12. Mekontchou Yomba, D. Yoan L. Topology Preserving Nonlinear Image Registration.

Degree: 2019, Drexel University

URL: https://idea.library.drexel.edu/islandora/object/idea%3A9470

►

Image Registration is an algorithmic optimization process primarily aimed at estimating the most optimal transformation from one image's coordinate plane onto another. Nonlinear image registration… (more)

▼

Image Registration is an algorithmic optimization process primarily aimed at estimating the most optimal transformation from one image's coordinate plane onto another. Nonlinear image registration has been the subject of numerous research initiatives. This widespread focus on the topic has resulted in a variety of different registration methods, intrinsic novel findings, as well as application areas. Although many potential use cases exist, the main three typical applications for 2D and 3D registration methods include object tracking in a series of scans, interpatient registrations, and multi-modal registration. Substantial research efforts have also begun to observe the registration process in both constrained and unconstrained settings as well as applied focused work on the regularization and homeomorphic behavior of vector fields for more accurate registration results. In this thesis, we compare the registration accuracy of our log unbiased multi-resolution registration model against the model provided by Igor et al. [16]. We also compare the effects of various objective functions on the ultimate accuracy of our multiresolution registration framework. Additionally, we delineate the short-comings of the log unbiased model [16] and mathematically propose a method to further accommodate these shortcomings as well further enforce topology preservation and smoothness in the displacement fields in hopes of making the model more robust specifically in a continuous setting. Our multi-resolution method utilizes information theory to quantify the magnitude of deformations, generates intuitively correct deformation maps, and correctly represents non-smooth transformations. To demonstrate the efficacy of the proposed framework, we generalize the well known large-deformation viscous fluid model. We are able to show that our proposed multi-resolution scheme generates more accurate transformation maps compared to those generated using the plain viscous fluid model with fluid regularization. We examine the power of this model to detect real changes specifically as we compare its use with different matching functionals. The results presented in this work show that the unbiased methods have higher reproducibility and accuracy than conventional registration models. Numerical results are presented in chapter 4, 5, and 6.

M.S., Computer Engineering – Drexel University, 2019

Advisors/Committee Members: Peters, Christopher, 1968 November 19-, College of Engineering.

Subjects/Keywords: Computer Engineering; Image registration

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APA (6^th Edition):

Mekontchou Yomba, D. Y. L. (2019). Topology Preserving Nonlinear Image Registration. (Thesis). Drexel University. Retrieved from https://idea.library.drexel.edu/islandora/object/idea%3A9470

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mekontchou Yomba, D Yoan L. “Topology Preserving Nonlinear Image Registration.” 2019. Thesis, Drexel University. Accessed February 27, 2021. https://idea.library.drexel.edu/islandora/object/idea%3A9470.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mekontchou Yomba, D Yoan L. “Topology Preserving Nonlinear Image Registration.” 2019. Web. 27 Feb 2021.

Vancouver:

Mekontchou Yomba DYL. Topology Preserving Nonlinear Image Registration. [Internet] [Thesis]. Drexel University; 2019. [cited 2021 Feb 27]. Available from: https://idea.library.drexel.edu/islandora/object/idea%3A9470.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mekontchou Yomba DYL. Topology Preserving Nonlinear Image Registration. [Thesis]. Drexel University; 2019. Available from: https://idea.library.drexel.edu/islandora/object/idea%3A9470

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Alberta

13. Popuri, Karteek. A unified FEM-based framework for medical image registration and segmentation.

Degree: PhD, Department of Computing Science, 2013, University of Alberta

URL: https://era.library.ualberta.ca/files/0z708w85q

► Medical image registration and segmentation are challenging because, medical images are generally corrupted by noise, image artifacts and the various anatomical regions of interest in… (more)

▼ Medical image registration and segmentation are challenging because, medical images are generally corrupted by noise, image artifacts and the various anatomical regions of interest in medical images often do not have distinct sharp boundaries. However, these anatomical regions frequently exhibit consistent shape and topological characteristics which is an advantage when compared to natural images. In our proposed work, we take into account the above mentioned aspects and devise automatic registration and segmentation methods using the popular energy minimization framework, with an application to medical images. In contrast to the widely used level set based segmentation approach, we follow the template-based segmentation approach, which is more suitable for medical images as it can easily handle multi-region segmentation and also has the desirable property of preserving the known topology of the anatomical structures. However, unlike the traditional template-based segmentation and registration methods that use uniform meshes along with the finite difference method (FDM) to solve the partial differential equations (PDEs) that arise in these methods, we use the finite element method (FEM) and solve the PDEs on a non-uniform mesh to obtain solutions whose accuracy is well adapted to the salient features in the image domain. In this work, we present a unified FEM-based registration and segmentation framework where the goal is to estimate a deformation field following the minimization of an energy that consists of a common diffusion-based regularization term and data term that depends on the appropriate segmentation or registration objective. Further, we extend this framework through the incorporation of an additional shape prior based regularization term that is learned from training data. Lastly, we propose a novel variational formulation for discrete deformable registration and show that interestingly it can be cast into our unified FEM-based registration and segmentation framework. We validated our proposed unified FEM-based segmentation and registration framework on real medical images including some of the popular benchmark datasets. We present a thorough evaluation of the various registration and segmentation algorithms developed in our work by comparing their performance with the other established methods in image registration and segmentation.

Subjects/Keywords: Finite element method; Image registration; Image segmentation

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

APA (6^th Edition):

Popuri, K. (2013). A unified FEM-based framework for medical image registration and segmentation. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/0z708w85q

Chicago Manual of Style (16^th Edition):

Popuri, Karteek. “A unified FEM-based framework for medical image registration and segmentation.” 2013. Doctoral Dissertation, University of Alberta. Accessed February 27, 2021. https://era.library.ualberta.ca/files/0z708w85q.

MLA Handbook (7^th Edition):

Popuri, Karteek. “A unified FEM-based framework for medical image registration and segmentation.” 2013. Web. 27 Feb 2021.

Vancouver:

Popuri K. A unified FEM-based framework for medical image registration and segmentation. [Internet] [Doctoral dissertation]. University of Alberta; 2013. [cited 2021 Feb 27]. Available from: https://era.library.ualberta.ca/files/0z708w85q.

Council of Science Editors:

Popuri K. A unified FEM-based framework for medical image registration and segmentation. [Doctoral Dissertation]. University of Alberta; 2013. Available from: https://era.library.ualberta.ca/files/0z708w85q

Vanderbilt University

14. Collins, Jarrod Alan. Uncertainty in Image-to-Physical Registration for Soft-Tissue Image Guided Surgery.

Degree: MS, Biomedical Engineering, 2015, Vanderbilt University

URL: http://hdl.handle.net/1803/14664

► Image-guided surgical methods have been investigated as techniques to increase the localization accuracy of hepatic cancer treatments such as resection and ablation. Mathematical registration methods… (more)

Subjects/Keywords: surgical navigation; registration; surface registration; image guided liver surgery; image-guidance

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

APA (6^th Edition):

Collins, J. A. (2015). Uncertainty in Image-to-Physical Registration for Soft-Tissue Image Guided Surgery. (Thesis). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14664

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Collins, Jarrod Alan. “Uncertainty in Image-to-Physical Registration for Soft-Tissue Image Guided Surgery.” 2015. Thesis, Vanderbilt University. Accessed February 27, 2021. http://hdl.handle.net/1803/14664.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Collins, Jarrod Alan. “Uncertainty in Image-to-Physical Registration for Soft-Tissue Image Guided Surgery.” 2015. Web. 27 Feb 2021.

Vancouver:

Collins JA. Uncertainty in Image-to-Physical Registration for Soft-Tissue Image Guided Surgery. [Internet] [Thesis]. Vanderbilt University; 2015. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/1803/14664.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Collins JA. Uncertainty in Image-to-Physical Registration for Soft-Tissue Image Guided Surgery. [Thesis]. Vanderbilt University; 2015. Available from: http://hdl.handle.net/1803/14664

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

15. Schut, Dirk (author). Automatic Initialization for 3D Ultrasound CT Registration During Liver Tumor Ablations.

Degree: 2018, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:97cded9d-50d2-4bb3-a130-835fdec48e5a

►

Ablation is a medical procedure to treat liver cancer where a needle-like catheter has to be inserted into a tumor, which will then be heated… (more)

Subjects/Keywords: Image registration; Image fusion; Ablation; 3D Ultrasound; Registration initialization; Medical imaging

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APA (6^th Edition):

Schut, D. (. (2018). Automatic Initialization for 3D Ultrasound CT Registration During Liver Tumor Ablations. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:97cded9d-50d2-4bb3-a130-835fdec48e5a

Chicago Manual of Style (16^th Edition):

Schut, Dirk (author). “Automatic Initialization for 3D Ultrasound CT Registration During Liver Tumor Ablations.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:97cded9d-50d2-4bb3-a130-835fdec48e5a.

MLA Handbook (7^th Edition):

Schut, Dirk (author). “Automatic Initialization for 3D Ultrasound CT Registration During Liver Tumor Ablations.” 2018. Web. 27 Feb 2021.

Vancouver:

Schut D(. Automatic Initialization for 3D Ultrasound CT Registration During Liver Tumor Ablations. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:97cded9d-50d2-4bb3-a130-835fdec48e5a.

Council of Science Editors:

Schut D(. Automatic Initialization for 3D Ultrasound CT Registration During Liver Tumor Ablations. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:97cded9d-50d2-4bb3-a130-835fdec48e5a

NSYSU

16. Yao, Yu-ting. Using Fringe Projection technique to form a high-resolution image from multiple low-resolution image.

Degree: Master, Electro-Optical Engineering, 2012, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0731112-182101

► This paper presents a set of Image Registration, Image Integration, interpolation and image restoration and other technology, the number of low-resolution images synthesized high-resolution image.… (more)

Subjects/Keywords: image registration; super resolution image; image restoration; interpolation; image integration

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APA (6^th Edition):

Yao, Y. (2012). Using Fringe Projection technique to form a high-resolution image from multiple low-resolution image. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0731112-182101

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Yao, Yu-ting. “Using Fringe Projection technique to form a high-resolution image from multiple low-resolution image.” 2012. Thesis, NSYSU. Accessed February 27, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0731112-182101.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Yao, Yu-ting. “Using Fringe Projection technique to form a high-resolution image from multiple low-resolution image.” 2012. Web. 27 Feb 2021.

Vancouver:

Yao Y. Using Fringe Projection technique to form a high-resolution image from multiple low-resolution image. [Internet] [Thesis]. NSYSU; 2012. [cited 2021 Feb 27]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0731112-182101.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yao Y. Using Fringe Projection technique to form a high-resolution image from multiple low-resolution image. [Thesis]. NSYSU; 2012. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0731112-182101

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Waterloo

17. Rincon, Jose. Facilitating Breast Conserving Surgery Using Preoperative MRI.

Degree: 2018, University of Waterloo

URL: http://hdl.handle.net/10012/13886

► Breast cancer is currently considered the most widespread malignancy in women, which costs the lives of approximately 400,000 people annually worldwide. While extremely useful for… (more)

▼ Breast cancer is currently considered the most widespread malignancy in women, which costs the lives of approximately 400,000 people annually worldwide. While extremely useful for early detection and diagnosis of breast disease, the application of MRI to pre-operative planning of breast conservative surgeries is complicated due to the differences in the patient's posture at the time of imaging and surgery, respectively. Specifically, while MRI is standardly performed with patients positioned with their face down and their breast unrestricted and pendulous, breast surgeries normally require the patients to lie on their back, in which case the breast undergoes substantial deformations due to the effect of gravity. As a result of these deformations, pre-surgical MRI images frequently do not correspond with the actual anatomy of the breast at the time of surgery, which limits their applicability to pre-surgical planning. Accordingly, to overcome the above problem and make the MRI images align with the actual intra-surgical anatomy of the breast, the images need to be properly warped - a procedure that is known as prone-to-supine image registration. In many cases, this registration is carried out in two steps, prediction and correction. While the former involves bio-mechanical modeling used to describe the principal effect of tissue deformation, the latter refines the preceding results based on the image content. What is more important, however, is the fact that the accuracy of the correction step (and, hence, of the registration process as a whole) is strongly dependent on the accuracy of bio-mechanical modeling, which needs therefore be maximized as much as possible. Consequently, the fundamental objective of this research project has been the development of algorithmic solutions for reliable and accurate prediction. In particular, we propose an automatic detection of the location and geometry of the breast, and a breast image segmentation method to differentiate between adipose and dense tissue that is tractable, stable, and independent of initialization.

Subjects/Keywords: prone to supine breast mri registration; image registration; image segmentation; breast mri; image processing

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

APA (6^th Edition):

Rincon, J. (2018). Facilitating Breast Conserving Surgery Using Preoperative MRI. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13886

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Rincon, Jose. “Facilitating Breast Conserving Surgery Using Preoperative MRI.” 2018. Thesis, University of Waterloo. Accessed February 27, 2021. http://hdl.handle.net/10012/13886.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Rincon, Jose. “Facilitating Breast Conserving Surgery Using Preoperative MRI.” 2018. Web. 27 Feb 2021.

Vancouver:

Rincon J. Facilitating Breast Conserving Surgery Using Preoperative MRI. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/10012/13886.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rincon J. Facilitating Breast Conserving Surgery Using Preoperative MRI. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13886

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Sydney

18. Zheng, Chaojie. Deformable Image Registration with Uncertainty-Awareness .

Degree: 2019, University of Sydney

URL: http://hdl.handle.net/2123/20948

► The popularization of information-sensing devices and rapid development of data storage and computing capability have launched the ongoing data explosion, and the value of such… (more)

Subjects/Keywords: image registration; deformable registration; registration uncertainty; demons; laminar flow; multiview collaborative learning

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APA (6^th Edition):

Zheng, C. (2019). Deformable Image Registration with Uncertainty-Awareness . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/20948

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Zheng, Chaojie. “Deformable Image Registration with Uncertainty-Awareness .” 2019. Thesis, University of Sydney. Accessed February 27, 2021. http://hdl.handle.net/2123/20948.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Zheng, Chaojie. “Deformable Image Registration with Uncertainty-Awareness .” 2019. Web. 27 Feb 2021.

Vancouver:

Zheng C. Deformable Image Registration with Uncertainty-Awareness . [Internet] [Thesis]. University of Sydney; 2019. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/2123/20948.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zheng C. Deformable Image Registration with Uncertainty-Awareness . [Thesis]. University of Sydney; 2019. Available from: http://hdl.handle.net/2123/20948

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Toronto

19. Tong, Hoi-Ki. Quantification of Vertebral Trabecular Bone Strain Via Feature Based Image Registration.

Degree: 2015, University of Toronto

URL: http://hdl.handle.net/1807/70717

►

Image based strain measurement within whole bone structures can be used to better understand fracture risk under load. This project aims to apply feature registration… (more)

Subjects/Keywords: Feature Registration; Image Registration; Meshless Method; microCT; Strain; Trabecular Bone; 0541

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

APA (6^th Edition):

Tong, H. (2015). Quantification of Vertebral Trabecular Bone Strain Via Feature Based Image Registration. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/70717

Chicago Manual of Style (16^th Edition):

Tong, Hoi-Ki. “Quantification of Vertebral Trabecular Bone Strain Via Feature Based Image Registration.” 2015. Masters Thesis, University of Toronto. Accessed February 27, 2021. http://hdl.handle.net/1807/70717.

MLA Handbook (7^th Edition):

Tong, Hoi-Ki. “Quantification of Vertebral Trabecular Bone Strain Via Feature Based Image Registration.” 2015. Web. 27 Feb 2021.

Vancouver:

Tong H. Quantification of Vertebral Trabecular Bone Strain Via Feature Based Image Registration. [Internet] [Masters thesis]. University of Toronto; 2015. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/1807/70717.

Council of Science Editors:

Tong H. Quantification of Vertebral Trabecular Bone Strain Via Feature Based Image Registration. [Masters Thesis]. University of Toronto; 2015. Available from: http://hdl.handle.net/1807/70717

University of Toronto

20. Shojaii, Rushin. Reconstruction of 3D Histology Volumes from Breast Lumpectomy Specimens.

Degree: PhD, 2017, University of Toronto

URL: http://hdl.handle.net/1807/82638

► Three dimensional reconstruction and examination of microscopic images of tissue sections can enhance the study of normal and disease processes, particularly in studies concerned with… (more)

▼ Three dimensional reconstruction and examination of microscopic images of tissue sections can enhance the study of normal and disease processes, particularly in studies concerned with structural changes. 3D histology volumes can also be used as ground truth in validating new volumetric medical imaging techniques. The accuracy of the histology volume reconstruction is hindered by sparse sampling of the clinical specimens, the deformation of the tissue during the histology processes, and variations in staining. The existing methods for histology volume construction of human breast specimens are either manual or applicable only to small cropped densely sampled regions. In this thesis, we hypothesize that by using image registration algorithms, 3D histology volumes can be automatically reconstructed from stacked 2D images of histology sections. We present an image registration framework for histology volume reconstruction, which is also extendable for registration of the histology to ex vivo medical images. The framework is first validated using a pre-clinical model and then further improved by optimizing the deformable registration for histology images obtained from highly deformable human breast specimens. Finally, the histology volumes of five lumpectomy specimens are reconstructed using the proposed framework to study tumour features in 3D, specifically tumour volume and focality. The proposed approach is shown to be suitable for 3D histology volume reconstruction from 2D histology images of breast lumpectomy specimens. The average target registration error for the breast specimens was measured as 0.47 Âą 0.31 mm based on manually selected landmarks and the optimized deformable registration was shown to significantly improve the registration comparing to rigid registration. It is also shown that this method has the potential to provide more accurate information about 3D tumour measurements, such as volume, and presence of multi-focality. Advisors/Committee Members: Martel, Anne L, Medical Biophysics.

Subjects/Keywords: Breast histology; Deformable registration; Histology image registration; Histology volume reconstruction; 0574

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

APA (6^th Edition):

Shojaii, R. (2017). Reconstruction of 3D Histology Volumes from Breast Lumpectomy Specimens. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/82638

Chicago Manual of Style (16^th Edition):

Shojaii, Rushin. “Reconstruction of 3D Histology Volumes from Breast Lumpectomy Specimens.” 2017. Doctoral Dissertation, University of Toronto. Accessed February 27, 2021. http://hdl.handle.net/1807/82638.

MLA Handbook (7^th Edition):

Shojaii, Rushin. “Reconstruction of 3D Histology Volumes from Breast Lumpectomy Specimens.” 2017. Web. 27 Feb 2021.

Vancouver:

Shojaii R. Reconstruction of 3D Histology Volumes from Breast Lumpectomy Specimens. [Internet] [Doctoral dissertation]. University of Toronto; 2017. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/1807/82638.

Council of Science Editors:

Shojaii R. Reconstruction of 3D Histology Volumes from Breast Lumpectomy Specimens. [Doctoral Dissertation]. University of Toronto; 2017. Available from: http://hdl.handle.net/1807/82638

Vanderbilt University

21. Chen, Antong. Automatic segmentation of structures in CT images for head and neck intensity-modulated radiation therapy.

Degree: PhD, Electrical Engineering, 2012, Vanderbilt University

URL: http://hdl.handle.net/1803/13583

► Cancers in the head and neck region account for approximately 3 percent of all cancers in the United States, as it is reported by the… (more)

Subjects/Keywords: IMRT; image registration; medical image processing; image segmentaiton; active shape model

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

APA (6^th Edition):

Chen, A. (2012). Automatic segmentation of structures in CT images for head and neck intensity-modulated radiation therapy. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/13583

Chicago Manual of Style (16^th Edition):

Chen, Antong. “Automatic segmentation of structures in CT images for head and neck intensity-modulated radiation therapy.” 2012. Doctoral Dissertation, Vanderbilt University. Accessed February 27, 2021. http://hdl.handle.net/1803/13583.

MLA Handbook (7^th Edition):

Chen, Antong. “Automatic segmentation of structures in CT images for head and neck intensity-modulated radiation therapy.” 2012. Web. 27 Feb 2021.

Vancouver:

Chen A. Automatic segmentation of structures in CT images for head and neck intensity-modulated radiation therapy. [Internet] [Doctoral dissertation]. Vanderbilt University; 2012. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/1803/13583.

Council of Science Editors:

Chen A. Automatic segmentation of structures in CT images for head and neck intensity-modulated radiation therapy. [Doctoral Dissertation]. Vanderbilt University; 2012. Available from: http://hdl.handle.net/1803/13583

University of Melbourne

22. LIANG, XI. Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging.

Degree: 2013, University of Melbourne

URL: http://hdl.handle.net/11343/52778

► Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast is a medical imaging tool used to detect and diagnose breast disease. A DCE-MR image is… (more)

▼ Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast is a medical imaging tool used to detect and diagnose breast disease. A DCE-MR image is a series of three-dimensional (3D) breast MRI scans. It is acquired to form a 4D image (3D spatial + time), before and after the injection of paramagnetic contrast agents. DCE-MRI allows the analysis of the intensity variation of magnetic resonance (MR) signals, before and after the injection of contrast agents over time. The interpretation of 4D DCE-MRI images can be time consuming due to the amount of information involved. Motion artifacts in between the image scans further complicate the diagnosis. A DCE-MR image includes a large amount of data and it is challenging to interpret even for an experienced radiologist. Therefore, a computer-aided diagnosis (CAD) system is desirable in assisting the diagnosis of abnormal findings in the DCE-MR image. We propose a fully automated CAD system that is comprised of five novel components: a new image registration method to recover motions in between MR image acquisitions, a novel lesion detection method to identify all suspicious regions, a new lesion segmentation method to draw lesion contours and a novel lesion feature characterization method. We then classify the automatically detected lesions using our proposed features. The following lists the challenges found in most CAD systems and the contributions in our CAD system of breast DCE-MRI. 1. Image registration. One challenge in the interpretation of DCEMRI is motion artifacts which cause the pattern of tissue enhancement to be unreliable. Image registration is used to recover rigid and nonrigid motions between the 3D image sequences in a 4D breast DCE-MRI. Most existing b-spline based registration methods require lesion segmentation in breast DCE-MRI to preserve the lesion volume before performing the registration. An automatic regularization coefficients generation method is proposed in the b-spline based registration of the breast DCE-MRI, where the tumor regions are transformed in a rigid fashion. Our method does not perform lesion segmentation but computes a map to reflect the tissue rigidity. In the evaluation of our proposed coefficients, the registration methods using our coefficients for rigidity terms are compared against manually assigned coefficients of the rigidity terms and smoothness terms. The evaluation is performed on 30 synthetic and 40 clinical pairs of pre- and post-contrast MRI scans. The results show that the tumor volumes can be well-preserved by using a rigidity term (2:25 +- 4:48% of volume changes) compared to a smoothness term (22:47% +- 20:1%). In our dataset, the volume preservation performance by using our automatically generated coefficients is comparable to the manually assigned rigidity coefficients (2:29% 13:25%), and show no significant difference in volume changes (p > 0:05). 2. Lesion detection. After the motions have been corrected by our registration method, we locate the region of interest (ROI) using our…

Subjects/Keywords: image processing; MRI; breast cancer; image registration; image segmentation

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

APA (6^th Edition):

LIANG, X. (2013). Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/52778

Chicago Manual of Style (16^th Edition):

LIANG, XI. “Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging.” 2013. Doctoral Dissertation, University of Melbourne. Accessed February 27, 2021. http://hdl.handle.net/11343/52778.

MLA Handbook (7^th Edition):

LIANG, XI. “Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging.” 2013. Web. 27 Feb 2021.

Vancouver:

LIANG X. Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging. [Internet] [Doctoral dissertation]. University of Melbourne; 2013. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/11343/52778.

Council of Science Editors:

LIANG X. Breast cancer detection and diagnosis in dynamic contrast-enhanced magnetic resonance imaging. [Doctoral Dissertation]. University of Melbourne; 2013. Available from: http://hdl.handle.net/11343/52778

Rochester Institute of Technology

23. Winkstern, Troy. Solving nonrigid registration with sliding and bending boundary conditions.

Degree: School of Mathematical Sciences (COS), 2011, Rochester Institute of Technology

URL: https://scholarworks.rit.edu/theses/4997

► In the past 20 years, there have been significant advances in the use of medical imaging in patient care. Today, image registration is being used… (more)

Subjects/Keywords: Boundary value problem; Diffusion regularizer; Image registration

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APA (6^th Edition):

Winkstern, T. (2011). Solving nonrigid registration with sliding and bending boundary conditions. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/4997

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Winkstern, Troy. “Solving nonrigid registration with sliding and bending boundary conditions.” 2011. Thesis, Rochester Institute of Technology. Accessed February 27, 2021. https://scholarworks.rit.edu/theses/4997.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Winkstern, Troy. “Solving nonrigid registration with sliding and bending boundary conditions.” 2011. Web. 27 Feb 2021.

Vancouver:

Winkstern T. Solving nonrigid registration with sliding and bending boundary conditions. [Internet] [Thesis]. Rochester Institute of Technology; 2011. [cited 2021 Feb 27]. Available from: https://scholarworks.rit.edu/theses/4997.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Winkstern T. Solving nonrigid registration with sliding and bending boundary conditions. [Thesis]. Rochester Institute of Technology; 2011. Available from: https://scholarworks.rit.edu/theses/4997

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Rochester Institute of Technology

24. Tuttle, Kevin. Registration of Diffusion Tensor Images in Log-Euclidean and Euclidean Space.

Degree: MS, School of Mathematical Sciences (COS), 2019, Rochester Institute of Technology

URL: https://scholarworks.rit.edu/theses/10184

► Diffusion Tensor Imaging is a type of Magnetic Resonance Imaging that allows for the examination of brain connectivity and axonal integrity. Diffusion Tensor Images… (more)

Subjects/Keywords: Diffusion tensor; DW-MRI; Image registration

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

APA (6^th Edition):

Tuttle, K. (2019). Registration of Diffusion Tensor Images in Log-Euclidean and Euclidean Space. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/10184

Chicago Manual of Style (16^th Edition):

Tuttle, Kevin. “Registration of Diffusion Tensor Images in Log-Euclidean and Euclidean Space.” 2019. Masters Thesis, Rochester Institute of Technology. Accessed February 27, 2021. https://scholarworks.rit.edu/theses/10184.

MLA Handbook (7^th Edition):

Tuttle, Kevin. “Registration of Diffusion Tensor Images in Log-Euclidean and Euclidean Space.” 2019. Web. 27 Feb 2021.

Vancouver:

Tuttle K. Registration of Diffusion Tensor Images in Log-Euclidean and Euclidean Space. [Internet] [Masters thesis]. Rochester Institute of Technology; 2019. [cited 2021 Feb 27]. Available from: https://scholarworks.rit.edu/theses/10184.

Council of Science Editors:

Tuttle K. Registration of Diffusion Tensor Images in Log-Euclidean and Euclidean Space. [Masters Thesis]. Rochester Institute of Technology; 2019. Available from: https://scholarworks.rit.edu/theses/10184

Universitat Autònoma de Barcelona

25. Mateo Prous, Xavier. Algorithms for the Multiple Variants of Registration in 3D Range Data.

Degree: Departament de Ciències de la Computació, 2013, Universitat Autònoma de Barcelona

URL: http://hdl.handle.net/10803/129097

► Ever since the photography was born, there exists a high interest in the possibility of detecting a third dimension in the images obtained by a… (more)

▼ Ever since the photography was born, there exists a high interest in the possibility of detecting a third dimension in the images obtained by a camera. This third dimension feature would allow the differentiation and easily filtering of the different objects present in the scene, and therefore to facilitate some of the main problematics in the computer vision research. In order to achieve this third dimension acquisition some techniques were historically applied, starting by the classical stereoscopy or other more current methods like Structure from Motion. During last years, the evolution of the technology has made possible the appearance of devices which allows the direct retrieval of 3D information without the manual intervention of the user. The use of different light spectrums like laser or infrared light and their integration inside the camera case have allowed this important improvement, accompanied at the same time by a reduction of the components price which allows its use for the vast majority of the research community. This thesis focuses on the main problems obtained in the use of the so-called range cameras, which, in addition to the usual RGB image, offers an additional image indicating the distance with respect to the objects in the scene. Thanks to the direct application of these range images, where each pixel corresponds to a distance, a 3D recreation of the observed scene can be directly obtained. One of the main advantages is that, if the camera is correctly calibrated, the 3D structure can be obtained with physical units of the real world (such as meters), and not with pixels. Nevertheless, the use of these range cameras was not as ideal as supposed. Usually some captures of every object in the scene are needed in order to obtain a full reconstruction, and different materials could produce problems that interferes the correct position of the object. The presence of these inconveniences produces the necessity of using some algorithms to produce a correct final 3D structure. The particularities of the 3D representation created from the range image become it appropriate to use as a support plate for placing other sources of information, like visible images or infrared images. The obtained 3D structure can be textured with these sources of information, giving an integrated result which could clarify some problems that cannot be solved by using the images separately. However, differences in the acquisition process between these types of images produce difficulties when they are fused. In addition, in order to obtain a full-side representation of a scene usually some 3D captures from different points of views are required. This addresses to the so-called multiview registration problem, where it is necessary to identify the position and orientation of the range camera for each viewpoint in order to correctly join the corresponding 3D structures. Current technology devices like GPSs or IMUs could give this information, but usually is not accurate enough, so common visual elements between different… Advisors/Committee Members: [email protected] (authoremail), true (authoremailshow), Binefa Valls, Xavier (director), Martí Gòdia, Enric (tutor), true (authorsendemail).

Subjects/Keywords: Range image; Registration; Bayesian; Tecnologies; 68

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

APA (6^th Edition):

Mateo Prous, X. (2013). Algorithms for the Multiple Variants of Registration in 3D Range Data. (Thesis). Universitat Autònoma de Barcelona. Retrieved from http://hdl.handle.net/10803/129097

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mateo Prous, Xavier. “Algorithms for the Multiple Variants of Registration in 3D Range Data.” 2013. Thesis, Universitat Autònoma de Barcelona. Accessed February 27, 2021. http://hdl.handle.net/10803/129097.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mateo Prous, Xavier. “Algorithms for the Multiple Variants of Registration in 3D Range Data.” 2013. Web. 27 Feb 2021.

Vancouver:

Mateo Prous X. Algorithms for the Multiple Variants of Registration in 3D Range Data. [Internet] [Thesis]. Universitat Autònoma de Barcelona; 2013. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/10803/129097.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mateo Prous X. Algorithms for the Multiple Variants of Registration in 3D Range Data. [Thesis]. Universitat Autònoma de Barcelona; 2013. Available from: http://hdl.handle.net/10803/129097

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

KTH

26. Joos, Louis. Deformable 3D Brain MRI Registration with Deep Learning.

Degree: Biotechnology and Health (CBH), 2019, KTH

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-262852

► Traditional deformable registration methods have achieved impressive performances but are computationally time-consuming since they have to optimize an objective function for each new pair… (more)

Subjects/Keywords: Deep Learning; Image Registration; Medical Engineering; Medicinteknik

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APA (6^th Edition):

Joos, L. (2019). Deformable 3D Brain MRI Registration with Deep Learning. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-262852

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Joos, Louis. “Deformable 3D Brain MRI Registration with Deep Learning.” 2019. Thesis, KTH. Accessed February 27, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-262852.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Joos, Louis. “Deformable 3D Brain MRI Registration with Deep Learning.” 2019. Web. 27 Feb 2021.

Vancouver:

Joos L. Deformable 3D Brain MRI Registration with Deep Learning. [Internet] [Thesis]. KTH; 2019. [cited 2021 Feb 27]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-262852.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Joos L. Deformable 3D Brain MRI Registration with Deep Learning. [Thesis]. KTH; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-262852

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

27. Ji, Chenhong (author). Nonrigid Image Registration using 3D Convolutional Neural Network with Application to Brain MR images.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:f99b402f-be89-4d53-ae6c-01ecc05a7f9e

►

Image registration is a vital tool in medical image analysis with a large number of applications assisting the medical experts. Currently, conventional image registration approach… (more)

Subjects/Keywords: MRI images; Image registration; Deep learning

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APA (6^th Edition):

Ji, C. (. (2019). Nonrigid Image Registration using 3D Convolutional Neural Network with Application to Brain MR images. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:f99b402f-be89-4d53-ae6c-01ecc05a7f9e

Chicago Manual of Style (16^th Edition):

Ji, Chenhong (author). “Nonrigid Image Registration using 3D Convolutional Neural Network with Application to Brain MR images.” 2019. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:f99b402f-be89-4d53-ae6c-01ecc05a7f9e.

MLA Handbook (7^th Edition):

Ji, Chenhong (author). “Nonrigid Image Registration using 3D Convolutional Neural Network with Application to Brain MR images.” 2019. Web. 27 Feb 2021.

Vancouver:

Ji C(. Nonrigid Image Registration using 3D Convolutional Neural Network with Application to Brain MR images. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:f99b402f-be89-4d53-ae6c-01ecc05a7f9e.

Council of Science Editors:

Ji C(. Nonrigid Image Registration using 3D Convolutional Neural Network with Application to Brain MR images. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:f99b402f-be89-4d53-ae6c-01ecc05a7f9e

Delft University of Technology

28. Bouter, P.A. (author). Designing the Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm and Applying it to Substantially Improve the Efficiency of Multi-Objective Deformable Image Registration.

Degree: 2016, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:c6eeb03d-2681-46b6-a12a-58433eddd3a2

►

The recently introduced Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) for discrete variables has been shown to be able to efficiently and effectively exploit the decomposability… (more)

Subjects/Keywords: optimal mixing; evolutionary algorithms; deformable image registration

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APA (6^th Edition):

Bouter, P. A. (. (2016). Designing the Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm and Applying it to Substantially Improve the Efficiency of Multi-Objective Deformable Image Registration. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:c6eeb03d-2681-46b6-a12a-58433eddd3a2

Chicago Manual of Style (16^th Edition):

Bouter, P A (author). “Designing the Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm and Applying it to Substantially Improve the Efficiency of Multi-Objective Deformable Image Registration.” 2016. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:c6eeb03d-2681-46b6-a12a-58433eddd3a2.

MLA Handbook (7^th Edition):

Bouter, P A (author). “Designing the Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm and Applying it to Substantially Improve the Efficiency of Multi-Objective Deformable Image Registration.” 2016. Web. 27 Feb 2021.

Vancouver:

Bouter PA(. Designing the Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm and Applying it to Substantially Improve the Efficiency of Multi-Objective Deformable Image Registration. [Internet] [Masters thesis]. Delft University of Technology; 2016. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:c6eeb03d-2681-46b6-a12a-58433eddd3a2.

Council of Science Editors:

Bouter PA(. Designing the Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm and Applying it to Substantially Improve the Efficiency of Multi-Objective Deformable Image Registration. [Masters Thesis]. Delft University of Technology; 2016. Available from: http://resolver.tudelft.nl/uuid:c6eeb03d-2681-46b6-a12a-58433eddd3a2

Washington University in St. Louis

29. Liao, Rui. Deformable Image Registration for Hyperspectral Images.

Degree: MS, Electrical & Systems Engineering, 2019, Washington University in St. Louis

URL: https://openscholarship.wustl.edu/eng_etds/436

► Image registration is one of the basic image processing operations in remote sensing. A hyperspectral image has two spatial dimensions and one spectral dimension.… (more)

Subjects/Keywords: Deformable Image Registration; Hyperspectral Images; Engineering

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APA (6^th Edition):

Liao, R. (2019). Deformable Image Registration for Hyperspectral Images. (Thesis). Washington University in St. Louis. Retrieved from https://openscholarship.wustl.edu/eng_etds/436

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Liao, Rui. “Deformable Image Registration for Hyperspectral Images.” 2019. Thesis, Washington University in St. Louis. Accessed February 27, 2021. https://openscholarship.wustl.edu/eng_etds/436.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Liao, Rui. “Deformable Image Registration for Hyperspectral Images.” 2019. Web. 27 Feb 2021.

Vancouver:

Liao R. Deformable Image Registration for Hyperspectral Images. [Internet] [Thesis]. Washington University in St. Louis; 2019. [cited 2021 Feb 27]. Available from: https://openscholarship.wustl.edu/eng_etds/436.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liao R. Deformable Image Registration for Hyperspectral Images. [Thesis]. Washington University in St. Louis; 2019. Available from: https://openscholarship.wustl.edu/eng_etds/436

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Louisiana State University

30. Xu, Huanhuan. Adaptive Stochastic Conjugate Gradient optimization for temporal medical image registration.

Degree: MS, Applied Mathematics, 2013, Louisiana State University

URL: etd-09032013-113122 ; https://digitalcommons.lsu.edu/gradschool_theses/324

► We propose an Adaptive Stochastic Conjugate Gradient (ASCG) optimization algorithm for temporal medical image registration. This method combines the advantages of Conjugate Gradient (CG) method… (more)

Subjects/Keywords: image registration; adaptive stochastic conjugate gradient optimizatio

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

APA (6^th Edition):

Xu, H. (2013). Adaptive Stochastic Conjugate Gradient optimization for temporal medical image registration. (Masters Thesis). Louisiana State University. Retrieved from etd-09032013-113122 ; https://digitalcommons.lsu.edu/gradschool_theses/324

Chicago Manual of Style (16^th Edition):

Xu, Huanhuan. “Adaptive Stochastic Conjugate Gradient optimization for temporal medical image registration.” 2013. Masters Thesis, Louisiana State University. Accessed February 27, 2021. etd-09032013-113122 ; https://digitalcommons.lsu.edu/gradschool_theses/324.

MLA Handbook (7^th Edition):

Xu, Huanhuan. “Adaptive Stochastic Conjugate Gradient optimization for temporal medical image registration.” 2013. Web. 27 Feb 2021.

Vancouver:

Xu H. Adaptive Stochastic Conjugate Gradient optimization for temporal medical image registration. [Internet] [Masters thesis]. Louisiana State University; 2013. [cited 2021 Feb 27]. Available from: etd-09032013-113122 ; https://digitalcommons.lsu.edu/gradschool_theses/324.

Council of Science Editors:

Xu H. Adaptive Stochastic Conjugate Gradient optimization for temporal medical image registration. [Masters Thesis]. Louisiana State University; 2013. Available from: etd-09032013-113122 ; https://digitalcommons.lsu.edu/gradschool_theses/324

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Open Access Theses and Dissertations