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1.
Deep Learning Methods for Medical Image Computing
by Liao, Haofu, Ph.D.  University of Rochester. 2019: 237 pages; 27737049.
2.
Enabling urgent computing within the existing distributed computing infrastructure
by Trebon, Nicholas, Ph.D.  The University of Chicago. 2011: 135 pages; 3472964.
5.
Registration of Pre- and Post-Treatment Brain Images with Missing Correspondences
by Dvornek, Nicha Chitphakdithai, Ph.D.  Yale University. 2012: 161 pages; 3535400.
6.
Using Spammers' Computing Resources for Volunteer Computing
by Bui, Thai Le Quy, M.S.  Portland State University. 2014: 90 pages; 1553892.
7.
Surface-based image segmentation using application-specific priors
by Veni, Gopalkrishna, Ph.D.  The University of Utah. 2016: 122 pages; 10248529.
8.
Longitudinal Tissue Segmentation Methods for the Aging Brain
by Schwarz, Christopher George, Ph.D.  University of California, Davis. 2012: 148 pages; 3540732.
9.
Graphical User Interface for the CVIP MATLAB Toolbox with Application to Syrinx Detection in Veterinary Thermographic Images
by Cuellar Buritica, Julian Rene, M.S.  Southern Illinois University at Edwardsville. 2019: 132 pages; 13900325.
11.
Hybrid deformable image registration - with application to brains, pelvises, and statistical atlases
by Ellingsen, Lotta Maria, Ph.D.  The Johns Hopkins University. 2008: 196 pages; 3309813.
13.
Kidney segmentat ion and image analysis in autosomal dominant polycystic kidney disease
by Warner, Joshua Dale, Ph.D.  College of Medicine - Mayo Clinic. 2016: 267 pages; 10111486.
14.
3D Image Registration of Dental Cone Beam Computed Tomography (CBCT) for Dental Treatment Recovery
by Rannulu, Chinthaka, M.S.  Southern Illinois University at Edwardsville. 2019: 82 pages; 13866151.
15.
Robust Image-Based Modeling and Simulation in Biomechanics
by Hafez, Omar Mohamed, Ph.D.  University of California, Davis. 2018: 151 pages; 10746888.
16.
Deep Learning for Segmented Medical Image Analysis
by Cheong, Vincent K., M.S.  California State University, Long Beach. 2019: 53 pages; 13858079.
17.
Image-based tissue growth modeling and prediction
by Nordquist, Andrew L., M.S.  The University of Texas at San Antonio. 2013: 120 pages; 1550349.
18.
Medical Cloud Show-Me System App
by Lin, Kenny, M.S.  California State University, Long Beach. 2013: 153 pages; 1524136.
19.
Complex-Valued Deep Learning With Applications to Magnetic Resonance Image Synthesis
by Virtue, Patrick M., Ph.D.  University of California, Berkeley. 2019: 153 pages; 22619704.
20.
Improved region of interest imaging
by Panse, Ashish, Ph.D.  State University of New York at Buffalo. 2012: 116 pages; 3541144.
22.
High-throughput Visual Knowledge Analysis and Retrieval in Big Data Ecosystems
by Cao, Hongfei, Ph.D.  University of Missouri - Columbia. 2015: 121 pages; 13877134.
23.
Multimodal Deep Learning to Enhance the Practice of Radiology
by Badgeley, Marcus Alexander, Ph.D.  Icahn School of Medicine at Mount Sinai. 2019: 236 pages; 10974774.
24.
Prediction of tumor deformation for Image Guided Radiation Therapy
by Hoog Antink, Christoph Bernhard, M.S.  State University of New York at Buffalo. 2011: 166 pages; 1495438.
25.
Coded Computing Systems Decoded: Dealing with Unreliability and Elasticity in Modern Computing
by Yang, Yaoqing, Ph.D.  Carnegie Mellon University. 2019: 271 pages; 13884004.
27.
MR Shuffling: Accelerated Single-Scan Multi-Contrast Magnetic Resonance Imaging
by Tamir, Jonathan I., Ph.D.  University of California, Berkeley. 2018: 150 pages; 10840304.
28.
Innovative and Age-Inclusive Interaction Design with Image-Schematic Metaphors
by Tscharn, Robert, Ph.D.  Bayerische Julius-Maximilians-Universitaet Wuerzburg (Germany). 2018: 240 pages; 13888568.
29.
Development and evaluation of quantitative Yttrium-90 bremsstrahlung spect methods
by Rong, Xing, Ph.D.  The Johns Hopkins University. 2013: 146 pages; 3572709.
30.
Precision and Selectivity: New Techniques in Image Guided Focused Ultrasound
by Chaplin, Vandiver L., Ph.D.  Vanderbilt University. 2018: 118 pages; 13834979.
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