DISCLAIMER:
Entry of taxonomy/keywords during proffered abstract submission was optional.
Not all abstracts will appear in search results.
| MO-E115-GePD-F1-2 | Chest X-Ray Quality Assurance Using Convolutional Networks: Identification of Clipped Images R McBeth1*, D Huo2 , (1) University of Colorado Hospital, Aurora, CO, (2) University Colorado Denver, School of Medicine, Aurora, CO |
| SU-F-207-6 | Whole Skeleton Statistical Appearance Models Applied to the Detection of Abnormal Bone in NaF PET/CT Images T Perk1*, M Scarpelli1 , T Bradshaw1 , S Chen2 , R Jeraj1,3 , (1) University of Wisconsin, Madison, WI (2) The 1st hospital of China Medical University, Shenyang, Liaoning (3) University of Ljubljana, Ljubljana, Slovenia |
| SU-H300-GePD-F6-3 | Development of An Automatic Deep Learning Framework for the Detection of Fiducial Markers in Intrafraction Kilovoltage Images A Mylonas1*, P J Keall1, J T Booth2, T Eade2, D T Nguyen1, (1) ACRF Image X Institute, Sydney Medical School, University of Sydney, Camperdown, New South Wales, Australia, (2) Northern Sydney Cancer Centre, Royal North Shore Hospital, St Leonards, New South Wales, Australia |
| SU-H300-GePD-F8-3 | Image Based Lung Cancer Phenotyping with Deep-Learning Radiomics T Chaunzwa1*, Y Xu2 , R Mak3 , D Christiani4 , M Lanuti5 , A Shafer6 , N Dia4 , H Aerts7 , (1) Howard Hughes Medical Institute, Chevy Chase, MD,(2) Harvard Medical School, Brigham and Women's Hosp., Boston, MA, (3) Brigham and Women's Hospital, Boston, MA, (4) Harvard T.H. Chan School of Public Health, Boston, MA, (5) Massachusetts General Hospital, Boston, MA, Boston, MA, (6) Boston, MA, (7) Dana-Farber/Brigham Women's Cancer Center, Boston, MA |
| SU-H300-GePD-F9-6 | Reproducibility of CT Iterative Reconstruction Algorithms From Analytic Reconstitutions with Convolutional Neural Networks for Pediatric Brain Imaging R MacDougall*, Y Zhang , H Yu , UMass Lowell, Lowell, MA |
| SU-I-GPD-I-6 | Impact of Image Pre-Processing On Radiomics Feature Prediction Power in Recurrence Glioblastoma Patients G Hajianfar1*, I Shiri2 ,M Oveisi3 , H Maleki4 , A Haghparast1 , (1) Kermanshah University of Medical Sciences,Kermanshah,Iran, (2)(3)(4) Rajaie Cardiovascular Medical and Research Center, Tehran,Iran |
| SU-I-GPD-J-67 | Densely Connected Semantic Segmentation Network for Liver Tumor Segmentation J Kwon*, E Shim , Y Kim , K Choi , Korea Institute of Science and Technology (KIST), Seoul, Seoul |
| SU-I-GPD-T-51 | An Artificial Intelligent (AI) Tool for Estimating the Output Factor of Electron Cutouts L Kofman1*, J Chang2 , (1) Tufts University, Medford, MA, (2) Northwell Health, Lake Success, NY |
| TH-EF-KDBRB1-6 | Abdominal Synthetic CT Generation for MR-Only Liver Radiotherapy Using Conditional Generative Adversarial Network J Fu1*, A Santhanam1 , M Cao1 , M Guo1 , K Singhrao1 , V Yu1 , D Ruan1 , D Low1 , J Lewis1 , (1) UCLA School of Medicine, Los Angeles, CA |
| TH-EF-KDBRB1-7 | Deep Learning Approaches for Male Pelvic Synthetic CT Generation Using 2D and 3D Convolutional Neural Networks J Fu*, Y Yang , K Singhrao , D Ruan , A Kishan , C King , D Low , J Lewis , UCLA, Los Angeles, CA |
| TU-C1000-GePD-F8-1 | Comparison of Automated PET Segmentation Methods in Lymphoma A Weisman1*, T Bradshaw1, Minnie Kieler1 R Jeraj1,2 (1) University of Wisconsin-Madison, Madison, WI, (2) University of Ljubljana, Ljubljana, Slovenia |
| TU-C1030-GePD-F1-3 | Comparison of Noise Analysis and Deep Learning-Based Image Quality Assessment (IQA) Methods for Thoracic Computed Tomography (CT) B Grant1*, J Lee2 , J Chung3 , I Reiser2 , L Lan2 , J Papaioannou3 , M Giger2 , (1) Western Kentucky University, Bowling Green, KY, (2) The University of Chicago, Chicago, IL, (3) University of Chicago Medicine, Chicago, IL, |
| TU-C930-GePD-F5-1 | Automatic Segmentation of Vertebrae Using Deep Learning and Generative Adversarial Networks E Boehnke*, A Santhanam , K Sheng , UCLA School of Medicine, Los Angeles, CA |
| TU-K-202-7 | Machine Learning On Quality Control of Chest CT Chest Exams: Scan Length Optimization D Huo*, A Scherzinger , University Colorado Denver, School of Medicine, Aurora, CO |
| WE-C1030-GePD-F5-3 | Generative Adversarial Network for Undersampled Brain MRI Reconstruction N Zhao*, K Sheng , UCLA School of Medicine, Los Angeles, CA |
| WE-FG-207-3 | Deep Learning for Automated Quantification of Tumor Phenotypes A Hosny1*, T Coroller1 , P Grossmann1 , C Parmar1 , R Zeleznik1 , A Kumar1 , J Bussink2 , R Gillies3 , R Mak4 , H Aerts1 , (1) Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women Hospital, Harvard Medical School, Boston, MA, (2) Radboud University, Nijmegen, Nijmegen, (3) Moffitt Cancer Center, Tampa, FL, (4) Brigham and Women's Hospital, Boston, MA |