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| SU-E-225BCD-2 | A Benchmark for Breast Ultrasound Image Computer-Aided Diagnosis E Zhang1*, J Li2 , S Seiler3 , M Chen4 , W Lu5 , X Gu6 , (1) UT Southwestern Medical Center, Dallas, TX, (2) Guangdong General Hospital, Guangzhou, China, (3) UT Southwestern Medical Center, Dallas, TX, (4) UT Southwestern Medical Center, Dallas, TX, (5) UT Southwestern Medical Center, Dallas, TX, (6) UT Southwestern Medical Center, Dallas, TX |
| SU-E-SAN2-6 | Variations in Feature Combinations Correlated with Radiation Pneumonitis Among Radiomics Software Packages J Foy*, S Armato , H Al-Hallaq , The University of Chicago, Chicago, IL |
| SU-G300-SPS-F4-4 | Comparison of Classifier Performance for Several Machine Learning Classification Tasks for Computer-Aided Diagnosis of Breast Cancer Using DCE-MRI M Vieceli1*, K Drukker2 , J Papaioannou2 , A Edwards2 , H Abe2 , M Giger2 , H Whitney1,2 , (1) Wheaton College, Wheaton, IL, (2) University of Chicago, Chicago, IL, |
| SU-I430-GePD-F9-3 | Initial Evaluation of the Use of a Convolutional Neural Network to Determine Coronary Artery Disease Severity Using Computed Tomography Angiography A Podgorsak1, 2*, K Sommer1, 2 , V Iyer3 , M Wilson1 , U Sharma1 , K Kumamaru3 , F Rybicki4 , D Mitsouras4 , E Angel5 , C Ionita1, 2 , (1) SUNY Buffalo, Buffalo, NY, (2) Canon Stroke and Vascular Research Center, Buffalo, NY, (3) Juntendo University, Tokyo, (4) University of Ottawa, Ottawa, ON, (5) Canon Medical Systems, Tustin, CA |
| SU-J400-CAMPUS-F2-3 | Pre-Treatment Prediction by Hormone Receptor Subtype of Response to Neoadjuvant Chemotherapy in Node-Positive Breast Cancer Patients; a Radiomics Study K Drukker*, A Edwards , C Doyle , J Papaioannou , K Kulkarni , M Giger , University of Chicago, Chicago, IL |
| TU-C930-GePD-F6-5 | A Comparison of Different Data Augmentation Methods in Isocitrate Dehydrogenase 1 (IDH1) Mutation Prediction H Xiao1*, Z Chang2 , (1) Duke Kunshan University, Kunshan, Jiangsu,(2) Duke University Medical Center, Durham, NC |
| TU-C930-GePD-F6-6 | Understanding the Impact of Heterogeneous Iterative Reconstruction and Dose Conditions in Low-Dose CT Computer-Aided Detection of Lung Nodules M Wahi-Anwar*, N Emaminejad , G Kim , M McNitt-Gray , M Brown , David Geffen School of Medicine at UCLA, Los Angeles, CA |
| TU-E-221AB-2 | A Comparison Study of Deep Learning Techniques for Mass Detection in Mammograms K Noro1*, X Zhang2 , H Takano3 , K Ichiji4 , N Homma5 , (1) Tohoku university, Sendai, 04, (2) Sendai National College of Technology, Sendai, ,(3) Tohoku University, Sendai, ,(4) Tohoku University, Sendai, 04, (5) Tohoku University, Sendai, |
| TU-F115-GePD-F8-4 | Prediction of Benign Or Malignant Breast Masses Using Texture Features From Digital Mammograms by Three Machine Learning Methods Y Cui12, Y Li3, J Zhu124*, J Dong2*,(1) Department of Radiation Oncology Physics and Technology,Shandong Cancer Hospital affiliated to Shandong University, Jinan 250117, China.(2)Shandong Provincial Key Laboratory of Network based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan 250022, China. (3) Department of Radiology, Shandong Cancer Hospital affiliated to Shandong University,Jinan 250117,China.(4) Shandong Medical Imaging and Radiotherapy Engineering Technology Research Center,Jinan 250117, China |
| WE-AB-225BCD-5 | Harmonization of Radiomic Features of Breast Lesions Extracted From DCE-MRI Across Two Populations H Whitney1,2*, H Li1 , Y Ji1,3 , A Edwards1 , J Papaioannou1 , P Liu3 , M Giger1 , (1) University of Chicago, Chicago, IL, (2) Wheaton College, Wheaton, IL,(3) Tianjin Medical University Cancer Institute and Hospital, Tianjin, China |
| WE-C1030-GePD-F5-2 | Automated Detection and Segmentation of Lung Tumors Using Deep Learning C Owens1,2*, D Rhee1,2 , D Fuentes3 , C Peterson2,4 , J Li5 , M Salehpour1 , L Court1,2,3 , J Yang1,2 , (1) Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, (2) The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX, (3) Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, (4) Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, (5) Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, TX |
| WE-FG-304-7 | Automated Quantification of Lymphoma On FDG PET/CT Images Using Cascaded Convolutional Neural Networks A Weisman1*, M Kieler1 , S Perlman1 , R Jeraj1,2 , M Hutchings3 , L Kostakoglu4 , T Bradshaw1 , (1) University of Wisconsin-Madison, Madison, WI, (2) Faculty of Mathematics and Physics, Ljubljana, Slovenia, (3) Rigshospitalet, Copenhagen, Denmark, (4) Mount Sinai Medical Center, New York, NY |
| WE-HI-303-3 | Breast Ultrasound Computer-Aided Diagnosis Using Triplet Path Networks with Fisher Discriminant Analysis E Zhang1*, Z Yang2 , S Seiler3 , S Yu4 , M Chen5 , W Lu6 , X Gu7 , (1) UTSouthwestern Medical Center, Dallas, TX, (2) UTSouthwestern Medical Center, Dallas, TX, (3) UTSouthwestern Medical Center, Dallas, TX, (4) Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, (5) UT Southwestern Medical Center, Dallas, TX, (6) UT Southwestern Medical Center, Dallas, TX, (7) UT Southwestern Medical Center, Dallas, TX |
| WE-HI-303-5 | Support Vector Machine in the Differential Diagnosis of Benign and Malignant Thyroid Nodules T Wang*, L Shi , W Lu , J Qiu , W Lu , Taishan Medical University, Taian, Shandong |
