DISCLAIMER:
Entry of taxonomy/keywords during proffered abstract submission was optional.
Not all abstracts will appear in search results.

Education | IM | IM/TH | Leadership | TH | show all

Taxonomy: Education: Analysis

MO-A-SAN4-0	Are You Prepared for Cybersecurity? What Industry Is Planning and How You Can Manage It L Tarbox1*, A Neff2*, R Kapoor3*, (1) University of Arkansas for Medical Sciences, Little Rock, AR, (2) MIM Software, Inc., (3) VCU Health System, Richmond, VA
MO-A-SAN4-1	DICOM Efforts to Improve CyberSecurity L Tarbox1*, A Neff2*, R Kapoor3*, (1) University of Arkansas for Medical Sciences, Little Rock, AR, (2) MIM Software, Inc., (3) VCU Health System, Richmond, VA
MO-A-SAN4-2	Industry Efforts to Improve CyberSecurity L Tarbox1*, A Neff2*, R Kapoor3*, (1) University of Arkansas for Medical Sciences, Little Rock, AR, (2) MIM Software, Inc., (3) VCU Health System, Richmond, VA
MO-A-SAN4-3	Coping with CyberSecurity: What can the clinical physicist do? L Tarbox1*, A Neff2*, R Kapoor3*, (1) University of Arkansas for Medical Sciences, Little Rock, AR, (2) MIM Software, Inc., (3) VCU Health System, Richmond, VA
MO-AB-SAN1-8	Fuzzy-Based Failure Modes and Effects Analysis (FMEA) for Ring-Gantry Linac IGRT J Chang*, S Jang , R Lalonde , D Heron , M Huq , UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine, Pittsburgh, PA
MO-AB-SAN2-0	AI for Predicting Response J Kalpathy-Cramer1*, M Giger2*, E Koay3*, J Wu4*, (1) ,Boston, MA, (2) University of Chicago, Chicago, IL, (3) MD Anderson, Houston, TX, (4) Stanford University, Palo Alto, CA
MO-AB-SAN2-1	AI for Predicting Treatment Outcomes J Kalpathy-Cramer1*, M Giger2*, E Koay3*, J Wu4*, (1) ,Boston, MA, (2) University of Chicago, Chicago, IL, (3) MD Anderson, Houston, TX, (4) Stanford University, Palo Alto, CA
MO-AB-SAN2-2	Radiomics and Machine Learning in Predicting Response From Medical Imaging J Kalpathy-Cramer1*, M Giger2*, E Koay3*, J Wu4*, (1) ,Boston, MA, (2) University of Chicago, Chicago, IL, (3) MD Anderson, Houston, TX, (4) Stanford University, Palo Alto, CA
MO-AB-SAN2-3	Quantitative Imaging Response Metrics for Hepatobiliary and Pancreatic Cancers J Kalpathy-Cramer1*, M Giger2*, E Koay3*, J Wu4*, (1) ,Boston, MA, (2) University of Chicago, Chicago, IL, (3) MD Anderson, Houston, TX, (4) Stanford University, Palo Alto, CA
MO-AB-SAN2-4	Spearhead Clinically Relevant Radiologic Biomarker Discovery in Precision Oncology with Habitat Imaging J Kalpathy-Cramer1*, M Giger2*, E Koay3*, J Wu4*, (1) ,Boston, MA, (2) University of Chicago, Chicago, IL, (3) MD Anderson, Houston, TX, (4) Stanford University, Palo Alto, CA
MO-E115-GePD-F2-4	Prediction of Acute Xerostomia Based On Delta Radiomics From CT Images During Radiation Therapy for Nasopharyngeal Cancer Yanxia LIU1*, Hongyu SHI1, Sijuan Huang2, Xiaochuan CHEN1, Huimin ZHOU2,3, Hui CHANG2, Yunfei XIA2, Guohua WANG1, Xin Yang2. (1) School of Software Engineering, South China University of Technology, Guangzhou, Guangdong, 510006, China. (2) Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, 510060, China. (3) Department of Oncology, the Seventy-fourth Group Army Hospital of the Chinese People's Liberation Army, Guangzhou, Guangdong, 510318, China.
MO-E115-GePD-F5-1	Comparison of 129Xe-MR Ventilation and 4DCT Ventilation Computed From the Deformation Vector Field J Fenoli*1, L Rankine1,2, B Driehuys2 , S Das1, (1) The University of North Carolina, Chapel Hill, NC, (2) Duke University, Durham, NC
MO-GH-SAN2-9	Improved Glioblastoma Survival Prediction Using Deep Learning-Based Radiomic Features From Preoperative Multimodal MR Images J Fu*, K Singhrao , X Zhong , X Qi , Y Yang , D Ruan , J Lewis , UCLA School of Medicine, Los Angeles, CA
MO-I345-GePD-F2-5	VMAT Plan Complexity Feature Analysis for Predicting Quality Assurance Outcomes Using Forests of Extremely Randomized Decision Trees P Wall1*, J Fontenot1,2 , (1) Louisiana State University, Baton Rouge, LA, (2) Mary Bird Perkins Cancer Center, Baton Rouge, LA
MO-I345-GePD-F4-5	Model of V12 to Number of Lesions and Total Tumor Volume in Multiple Brain Metastases Stereotactic Radiosurgery R He*, W Duggar , M Kanakamedala , A Fatemi , S Vijayakumar , C Yang , Department of Radiation Oncology, University of Mississippi Med. Center, Jackson, MS
MO-I345-GePD-F7-5	Retaining Novel Cases to Improve Model Robustness in a Case Based Reasoning Workflow for Radiation Therapy Planning Y Sheng1*, J Zhang1 , C Wang1 , F Yin1 , Q Wu1 , Y Ge2 , (1) Duke University Medical Center, Durham, NC, (2) University of North Carolina at Charlotte, Charlotte, NC
MO-J430-CAMPUS-F2-2	Deep Learning in Medical Physics: Reality Or Noise? G Valdes*, M Romero-Calvo , T Solberg , Y Interian , UCSF Comprehensive Cancer Center, San Francisco, CA
MO-J430-CAMPUS-F2-4	Machine Learning Method to Automate Structure Name Mapping W Sleeman IV1,3*, J Nalluri1,3 , S Khajamoinuddin2 , P Ghosh2 , M Hagan1,3 , J Palta1,3 , R Kapoor1,3 , (1) Virginia Commonwealth University, Department of Radiation Oncology, Richmond, VA (2) Virginia Commonwealth University, Department of Computer Science, Richmond, VA (3) National Radiation Oncology Program, Department of Veteran Affairs, Richmond, VA
MO-K-301-3	3D Validation of a Monte-Carlo Model of a Cyberknife System Dedicated to the Determination of Out-Of-Field Doses J Colnot1*, V Barraux2 , C Loiseau2 , A Batalla2 , R Gschwind3 , C Huet1 , (1) Institut de Radioprotection et de Surete Nucleaire, Fontenay-aux-Roses, France, (2) CLCC Francois Baclesse, Caen, France, (3) Universite de Franche-Comte, LCE UMR CNRS, Montbeliard, France
PO-GePV-E-4	Analysis of the Status Quo of LA (X Knife /γ Knife) Physicists in China Q Sun , L Shi*, W Lu , J Qiu , L Pei , Taishan Medical University, Taian, 37
PO-GePV-E-8	Application of Ultrasound Full-Waveform Inversion in Bone Quantitative Measurement M Suo , D Zhang* , Wuhan University, Wuhan, Hubei
PO-GePV-E-15	Employment Status Analysis of Applied Physics (Medical Physics Direction) Undergraduate Major Take Shandong First Medical University as An Example Q Sun1 , L Shi2*, W Lu3 , J Qiu4 , Y OuYang5 , (1) Taishan Medical University, Taian, ,(2) Taishan Medical University, Taian, ,(3) Taishan Medical University, Taian, ,(4) Taishan Medical University, Taian, Shandong, ,(5) Taishan Medical University, Taian, Shandong
PO-GePV-I-2	Developing in Vivo Diffusion and Functional MR Imaging Biomarkers in a Knock-in Mouse Model of DYT1 Dystonia H Liu*, D Vaillancourt , University of Florida, Gainesville, FL
PO-GePV-I-13	Augmentation of MRI Multi-Sequence Radiomics Data to Improvebrain Tumor Classification K Ogden1*, N Salastekar1 , D LaBella1 , A Chakraborty1 , E Oakes2 , R Mangla1 , (1) SUNY Upstate Medical Univ, Syracuse, NY, (2) Syracuse University, Syracuse, NY
PO-GePV-M-4	Utilizing Quantitative Local Trajectory Method to Online Analyse Intrafraction Prostate Motion Y Gao*, B Zhao , X Qi , X Gao , Peking University First Hospital, Beijing
PO-GePV-M-21	Extracting Heterogeneously Formatted Clinical Data From DICOM Secondary Capture Using OCR E Somasundaram*, S Brady , H Li , L He , T Maloney , J Dudley , J Dillman , Cincinnati Childrens Hospital Med Ctr, Cincinnati, OH
PO-GePV-P-85	Comparison of Manual Vs. Semi-Automatic CBCT Image Analysis L Claps*, P Alaei , University of Minnesota, Minneapolis, MN
PO-GePV-T-43	Geometrical Characterization of Medical Linear Accelerators with An Integrated Magnetic Resonance Imaging System H Riis1*, C Brink1,2 , A Bertelsen1 , U Bernchou1,2 , F Mahmood1,2 , Y Cho3 , D Moseley3 , (1) Laboratory of Radiation Physics, Odense University Hospital, DK-5000 Odense, Denmark, (2) Department of Clinical Research, University of Southern Denmark, DK-5000 Odense, Denmark, (3) Princess Margaret Cancer Centre, Toronto, Canada
PO-GePV-T-48	A Method To Identify Genetic Signature For Radiosensitivity Of Esophagus And To Model Esophagitis H Yao1*, W Wang1 , N Bi2 , S Jolly3 , P Fu1 , J Jin1,4 , F Kong1 , (1) Case Western Reserve University, Cleveland, OH, (2) National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, (3) University of Michigan, Ann Arbor, MI, (4) University Hospitals, Case Medical Center, Cleveland, OH
PO-GePV-T-69	Neutron Generation in Proton Passive Scattering Treatments D Ellis1*, Y Yeom2 , K Griffin2 , M Mille2 , C Lee3 , J Jung1 , C Lee2 , (1) East Carolina University, Greenville, NC, (2) National Cancer Institute, Rockville, MD, (3) University of Michigan, Ann Arbor, MI
PO-GePV-T-131	A Data Driven Retrospective Analysis of Couch Tolerances On Patients Positioned Using the Elekta Hexapod R George*, N Kirby , D Saenz , University of Texas Health Science at San Antonio, San Antonio, TX
PO-GePV-T-218	Discrimination of Photoneutron Generation Among Conventional Wedge and 3D-CRT Treatment Planning for Breast Cancer Practicing in a 10 and 15 MV Megavoltage X-Rays Beams H Ali sahib1 , G Bharanidharan2*, N Sekar3 , D Mohapatra4 , A Prakasarao5 , S Jagadeesan6 , J Vellingiri7 , G Singaravelu8 , p Mahadevan9 , K Karuppasamy10 , M Murgan11 , (1) Anna University, Chennai, ,(2) Anna University, Chennai, ,(3) Anna University, Chennai, ,(4) 2Reactor and Radiological Safety Section, Safety Research Institute - Atomi, Chennai, ,(5) Anna University, Chennai, ,(6) VPS Lakeshore Hospital, Kochi, ,(7) VPS Lakeshore Hospital, Kochi, ,(8) Anna University, Chennai, ,(9) VPS Lakeshore Hospital, Kochi, ,(10) VPS, Ernakulam, KL, (11) VPS Lakeshore Hospital, Kochi,
SU-E-221AB-2	A Relational Autoencoder for Retrieving Similar Patients in Radiotherapy Treatment Planning K Wang*, X Gu , M Chen , W Lu , UT Southwestern Medical Center, Dallas, TX
SU-E-221AB-4	Machine Learning in IMRT Plan Evaluation A Roy1*, D Cutright2 , M Gopalakrishnan3 , B Mittal3 , (1) The University of Texas at San Antonio, San Antonio, TX, (2) University of Chicago Medicine, Chicago, IL, (3) Northwestern Memorial Hospital, Chicago, IL
SU-E-221AB-6	Normalizing the Response of a Fixed Geometry EPID Using a Flattening Phantom On a Ring Gantry Linear Accelerator J Chapman*, E Laugeman , B Sun , N Knutson , S Goddu , G Hugo , S Mutic , B Cai , Washington University School of Medicine, St. Louis, MO
SU-E-302-4	Out-Of-Filed Doses of Neutrons Generated by Pencil-Beam-Scanning Protons Irradiating Proton-Tissue-Equivalent Materials C Correa Alfonso1*, E Olguin1 , E Macartney1 , W Bolch1 , W Hsi2 , Z Li2 , S Flampouri3 , (1) University of Florida, Gainesville, FL, (2) University of Florida Proton Therapy Institute, Jacksonville, FL, (3) Emory University, Atlanta, GA
SU-E-303-5	Transfer Learning From MR to CT for Prostate Segmentation Using 2.5D Unet Yucheng Liu1*, Yulin Liu2 , Michael Liu1, Rami Vanguri1, Joe Stember1, Jonathan Shoag3, Sachin Jambawalikar1 , (1) Columbia University Medical Center, New York, NY, (2) Chung Yuan Christian University, Taoyuan, Taiwan, (3)Weill Cornell Medicine, New York, NY
SU-E-SAN2-2	Comparison in Classification Performance of Radiation Pneumonitis Between Two Delta Radiomics Logistic Regression Models J Foy*, H Al-Hallaq , S Armato , The University of Chicago, Chicago, IL
SU-E-SAN2-4	Evaluating the Stability of Radiomics Features Using 4D-CT X Wang1*, C Ma1 , H Wang2 , Y Zhang1 , N Yue1 , K Nie1 , (1) Rutgers-Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, (2) Shanghai Chest Hospital, Shanghai Jiaotong University, Shanghai, China
SU-E-SAN2-5	Improving Prognostic Prediction for Lung Cancer Patients Who Underwent SBRT Using Breath-Hold Diagnostic CT-Based Image Features: A Retrospective Single Institutional Study R Kakino*, M Nakamura , T Mitsuyoshi , T Shintani , H Hirashima , Y Matsuo , T Mizowaki , Graduate School of Medicine, Kyoto University
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-E-SAN4-1	A Graphical User Interface (GUI) Toolkit for Treatment Plan Quality Analysis in Right Lung SBRT A Brito Delgado1*, K Rasmussen2 , K Kauweloa3 , T Medrano Pesqueira4 , D Cohen5 , T Eng6 , N Kirby7 , D Saenz8 , Z Shi9 , S Stathakis10 , N Papanikolaou11 , A Gutierrez12 , (1) University of Kansas Hospital, Overland Park, KS, (2) University of Texas HSC SA, San Antonio, TX, (3) University of Kansas Medical Center, Overland Park, KS, (4) Centro Estatal de Oncologia, Hermosillo, Sonora, Mexico ,(5) Jefferson Health New Jersey, Sewell, ,(6) Emory University, Atlanta, ,(7) University of Texas HSC SA, San Antonio, TX, (8) University of Texas HSC SA, San Antonio, TX, (9) University of Texas HSC SA, San Antonio, TX, (10) University Of Texas Health, San Antonio, TX, (11) University of Texas HSC SA, San Antonio, TX, (12) Miami Cancer Institute, Miami, FL
SU-F-225BCD-6	Using Neural Net Object Detection for Fiducial Tracking D Sawkey1*, H Mostafavi1, L Cervino2, (1) Varian Medical Systems, Palo Alto, CA (2) UC San Diego, La Jolla, CA
SU-F-SAN2-4	Feasibility of CT-Only 3D Dose Prediction for VMAT Prostate Plans Using Deep Learning S Willems1*, W Crijns1 , E Sterpin1,2 , K Haustermans1 , F Maes1 , (1) KULeuven (2) UCLouvain
SU-G300-SPS-F4-9	Validation of Production Standardizing Radiation Therapy Structures Names by the Content-Based Standardizing Nomenclatures (CBSN) in Radiation Oncology X MAI1,2*, S HUANG1,2 , S Huang1 , Y XIA1 , X HUANG1 , X Yang1 , (1) Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, 510060, China. (2) Xinhua College of Sun Yat-sen University, Guangzhou, Guangdong, 510520,China.
SU-I300-GePD-F5-2	Assessing Myocardial Perfusion After Cardiac Irradiation Using Dynamic Contrast Enhanced Hybrid PET/MRI O Chau1*, O El-Sherif2 , M Mouawad3 , F Prato4 , S Gaede5 , (1) London Regional Cancer Centre, London, ON, (2) Mayo Clinic, Rochester, MN, (3) Western University, London, ON, (4) Lawson Health Research Institute, London, ON, (5) London Regional Cancer Program, London, ON
SU-I300-GePD-F5-6	Lesion-Level Response Prediction From 18F-FDG PET/CT in Metastatic Melanoma Patients Treated with Immune Checkpoint Blockade D Huff1*, R Shah2 , A Weisman1 , L Zurbriggen3 , M Albertini3 , R Jeraj1,4 , (1) University of Wisconsin-Madison, Madison, WI, (2) North Memorial Healthcare, Robbinsdale, MN, (3) University of Wisconsin Carbone Cancer Center, Madison, WI, (4) University of Ljubljana, Ljubljana, Slovenia
SU-I400-GePD-F5-6	3D Dose Prediction Model for Head and Neck Cancer Patients by Combining Field Geometry Information with Patient Images E Czeizler*, M Hakala , S Basiri , E Kuusela , Varian Medical Systems Finland, Helsinki, 18
SU-I430-GePD-F6-2	Machine Learning Based Region of Interest Optimization Framework for Optical Surface Monitoring System: A Feasibility Study T Chen*, D Barbee , P Cohen , K Du , New York University, New York, NY
SU-I430-GePD-F8-1	Functional Networks in Health and Cancerous Brains Related to Language FMRI Q Li1*, G Ferraro1 , L Pasquini2 , K Peck2 , H Makse1 , A Holodny2 , (1) City College of New York, New York, NY, (2) Memorial Sloan Kettering Cancer Center, New York, NY.
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-F2-2	Observer-Independent, Hand-Crafted Radiomic Features Predict GBM Patient-Specific Survival E Carver1*, N Wen2 , E Liang3 , J Snyder4 , (1) Wayne State University, Troy, MI, (2) Henry Ford Hospital, Detroit, MI, (3) HFHS, Detroit, ,(4) HFHS, Detroit,
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
SU-K-225BCD-6	Improving CBCT Quality to CT Level Using Deep-Learning Method for Adaptive Radiation Therapy Y Zhang1,2*, N Yue1 , M Su2 , Y Ding3 , B Liu1 , Y Zhang1 , Y Zhou4 , K Nie1 , (1) Department of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, (2) Department of Radiological Science, University of California Irvine, Irvine, CA, (3) Hubei Cancer Hospital, Wuhan,(4) Fudan University Zhongshan Hospital, Shanghai
SU-K-301-7	Evaluation of Safety in IMRT Delivery Using Failure Mode and Effects Analysis F Akbari1*, D Raxter2 , D Shvydka3 , E Parsai4 , (1) University of Toledo, Toledo, OH, (2) University of Toledo, Toledo, OH, (3) University of Toledo Health Science Campus, Toledo, OH, (4) University of Toledo Medical Center, Toledo, OH
SU-K-303-1	Auto Segmentation of Organs at Risk in Thorax Computed Tomography Using Deep Convolutional Neural Networks M Haytmyradov1*, M Surucu1 , F Cassetta1 , J Roeske1 , (1) Loyola University Medical Center, Maywood, IL
SU-L-301-4	Implementation of TG-100 in a Large Network Organization: Initial Physics Plan Check V Misic*, K Wilson , R Surgent , E Brandner , M Huq , UPMC Hillman Cancer Center, Pittsburgh, PA
TH-A-221AB-11	A Method for Automated Repeat/reject Rate Analysis in CT S Rose*, B Viggiano , T Szczykutowicz , University Wisconsin-Madison, Madison, WI
TH-A-SAN2-2	Prediction of MGMT Status for Newly Diagnosed Glioblastoma Patients Using Radiomics Feature Extraction From 18F-DOPA PET Imaging J Qian*, M Herman , D Brinkmann , N Laack , P Korfiatis , B Kemp , C Hunt , V Lowe , D Pafundi , Mayo Clinic, Rochester, MN
TH-A-SAN2-10	Adaptive Margins with An Early Warning System for Motion-Tracking Errors in Liver SBRT M Liu1*, A Ross2 , J E Cygler1,3,4 , E Vandervoort1,3,4 (1) Department of Physics, Carleton University, Ottawa, ON, Canada (2) Department of Physics, McGill University, Montreal, QC, Canada (3) Department of Medical Physics, The Ottawa Hospital Cancer Centre, Ottawa, ON, Canada (4) Department of Radiology, University of Ottawa, Ottawa, ON, Canada
TH-B-SAN2-0	The Anne and Donald Herbert Distinguished Lectureship in Modern Statistical Modeling M Schipper1*, (1) University of Michigan, Ann Arbor, MI
TH-B-SAN2-1	Introduction M Schipper1*, (1) University of Michigan, Ann Arbor, MI
TH-B-SAN2-2	Individualized and Adaptive Radiation Therapy via Statistical Models M Schipper1*, (1) University of Michigan, Ann Arbor, MI
TH-B-SAN2-3	Q&A M Schipper1*, (1) University of Michigan, Ann Arbor, MI
TH-BC-225BCD-4	Automatic Fiducial Marker Detection in Prostate Cancer MR Images Using Generative Adversarial Networks (GANs) K Singhrao1*, J Fu1 , A Kishan1 , J Lewis1 , (1) Dept. of Radiation Oncology, UCLA, Los Angeles, CA,
TH-C-SAN2-1	Harmonizing Imaging Protocols: Impact On Radiomics Survival Prediction in Large Patient Cohorts R Ger*, S Zhou , D Mackin , H Elhalawani , B Elgohari , J Meier , C Fuller , R Howell , R Layman , H Li , O Mawlawi , R Stafford , L Court , UT MD Anderson Cancer Center, Houston, TX
TH-C-SAN2-2	Combination of Multiple Neural Networks Using Transfer Learning and Extensive Geometric Data Augmentation for Assessing Cellularity Scores in Histopathology Images J Beckmann*, K Popovic , Rose-Hulman Institute of Technology, Terre Haute, IN
TU-AB-225BCD-3	Dual Energy Bone Suppression Using Neural Networks M Haytmyradov1*, F Cassetta1, R Patel1, M Surucu1, H. Mostavafi2, J Roeske1, (1) Loyola University Medical Center, Maywood, IL, USA (2) Varian Medical Systems, Palo Alto, CA, USA
TU-AB-SAN2-4	Multi-Branch Convolutional Neural Network Combines Unregistered PET and CT Images for Head & Neck Cancer Outcome Prediction A Diamant*, A Chatterjee , M Vallieres , G Shenouda , J Seuntjens , McGill University Health Centre, Montreal, QC
TU-AB-SAN2-9	Investigating Radiomics to Predict Positive Lymph Nodes in Oral Cavity Squamous Cell Carcinoma (OSCC) A Traverso12*, A Hosni-Abdalaty2 , M Hasan2 , J Kim2 , J Ringash2 , J Cho2 , S Bratman2 , A Bailey2 , J Waldron9 , M Welch2 , J Irish3 , B O'Sullivan2 , J De Almeida3 , M Giuliani2 , D Chepeha2 , D Goldstein2 , D Jaffray2 , L Wee1 , A Dekker1 , A Hope2 , (1) MAASTRO Clinic, Maastricht, The Netherlands ,(2) Princess Margaret Cancer Centre, Toronto, Canada (3) University Health Network, Toronto, Canada
TU-AB-SAN2-11	ComBat Harmonization for Radiomcs Studies with CT Images R N Mahon1*, M Ghita1 , G D Hugo2 , E Weiss1 , (1) Virginia Commonwealth University, Richmond, VA, (2) Washington University School of Medicine, St. Louis, MO
TU-C1000-GePD-F2-5	Synthetic CT Generation Using Unpaired Images in a CycleGAN with Identity Loss Z Sun1 , S Baek1 , S Yaddanapudi1 , J St-Aubin1*, University of Iowa, Iowa City, IA
TU-C1000-GePD-F5-6	Uncertainties of Bladder Cancer Radiation Treatment with CT-On-Rails Localization T Lin*, C Ma , Fox Chase Cancer Center, Philadelphia, PA
TU-C1000-GePD-F6-2	Building Robust Machine Learning Models for Colorectal Cancer Risk Prediction B Nartowt1*, G Hart2 , W Muhammad3 , Y Liang4 , J Deng5 , (1) Yale/New Haven Hospital, New Haven, CT, (2) Yale University, New Haven, CT, (3) Yale School of Medicine, Yale University, New Haven, CT, (4) Medical College of Wisconsin, Milwaukee, WI, (5) Yale Univ. School of Medicine, New Haven, CT
TU-C1000-GePD-F6-6	Machine Learning Based Method for Peer Review Rounds Case Prioritization L Conroy*, C McIntosh , T Purdie , The Princess Margaret Cancer Centre - UHN, Toronto, ON
TU-C1030-GePD-F2-5	Synthetic CTs Generated by Deep Learning Approaches: How Good Are They for Radiomics Analysis? F Tixier*, P Klages , S Riyahi , J Jiang , H Um , N Tyagi , R Young , H Veeraraghavan , Memorial Sloan-Kettering Cancer Center, New York, NY
TU-C930-GePD-F6-2	Quantification of Pixel-Wise Uncertainty Associated with Automatic Segmentation D Ruan*, T Zhao , D Low , M Steinberg , UCLA, Los Angeles, CA
TU-C930-GePD-F6-3	Standardizing Patient Orientation to Improve Generalization of Radiomics Models A Iyer*, J Oh , M Thor , J Deasy , A Apte , Memorial Sloan Kettering Cancer Center, New York, NY
TU-C930-GePD-F6-4	The Stability of CT Radiomics Feature Using Repeated Scans C Ma1*, (1) Rutgers Cancer Institute of New Jersey
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-F7-6	Generalized Approach to Radiotherapy Treatment Planning by Directly Optimizing the Health Outcome Instead of Dose: Preliminary Results for External-Beam Prostate Radiotherapy L Wilson*, W Newhauser , Louisiana State University, Baton Rouge, LA
TU-E-SAN1-3	First Treatment Planning System for Routine, Personalized Whole-Body Dose Assessment for Megavoltage Photon Therapy L Wilson1*, W Newhauser1 , C Schneider1 , F Kamp2 , M Reiner2 , J Martins3 , G Landry3 , R Kapsch4 , K Parodi3 , (1) Louisiana State University, Baton Rouge, LA, (2) University Hospital, LMU Munich, Munich, (3) Ludwig-Maximilians-Universitat Munchen, Munich, (4) Physikalisch-Technische Bundesanstalt, Braunschweig,
TU-E-SAN4-0	The Integration of AI and Machine Learning in Medical Physics Applications V Kearney1*, M Chan2*, C Cardenas3*, (1) University of California San Francisco, San Francsico, CA, (2) Memorial Sloan Kettering Cancer Center, Basking Ridge, NJ, (3) University of Texas MD Anderson Cancer Center, Houston, TX
TU-F115-GePD-F2-1	Modeling Tumor Growth and Radiation Response with a Multi-Population, Diffusion-Based Model E Dahlman*, Y Watanabe , University of Minnesota, Minneapolis, MN
TU-F115-GePD-F9-1	Automatic Multi-Organ Segmentation On Female Pelvic CT with Dense V-Network Q Wu*, Peoples Liberation Army General HospitalBeijing
TU-HI-221AB-0	Biomedical Modeling Using Imaging Data P Boyle1*, D Tward2*, D Holdsworth3*, C Grassberger4*, (1) University of Washington, Seattle, WA, (2) The Johns Hopkins University, Baltimore, MD, (3) John P. Robarts Research Instit., London, ON, (4) Massachusetts General Hospital, Boston, MA
TU-HI-SAN2-9	Multiparametric Breast MRI Radiomics in Distinguishing Between Benign and Malignant Breast Lesions Q Hu1*, H Whitney1,2 , A Edwards1 , J Papaioannou1 , M Giger1 , (1) University of Chicago, Chicago, IL, (2) Wheaton College, Wheaton, IL
TU-HI-SAN4-9	Towards in Vivo Dosimetry with X-Ray Acoustic Computed Tomography (XACT) P Samant1*, Y Chen2 , S Wang1 , L Trevisi1 , S Ahmad2 , H Liu2 , L Xiang1 , (1) University of Oklahoma, Norman, OK, (2) University of Oklahoma Health Science Center, Oklahoma City, OK
WE-AB-221AB-5	Dual-Energy CT Ventilation & Perfusion Imaging as An Accessible Alternative to Nuclear Medicine Techniques J Korte* , N Bucknell , S Siva , B Woon , P Jackson , T Mulcahy , J Callahan , T Kron , N Hardcastle , Peter MacCallum Cancer Centre, Melbourne, Australia
WE-AB-225BCD-6	Intra-Treatment 18F-FDG PET/CT Radiomic Signature Predicts In-Field Recurrence Following Definitive Chemo-Radiation Therapy for Oropharyngeal Cancer K Lafata*, Y Chang , C Wang , Y Mowery , D Brizel , F Yin , Duke University Medical Center, Durham, NC
WE-AB-225BCD-7	Modeling Local Versus Distant Tumor Recurrence in Non-Small Cell Lung Cancer Patients Receiving Combined Chemoradiotherapy and Molecularly Targeted Drugs D McClatchy*, H Paganetti , H Willers , C Grassberger , Massachusetts General Hospital and Harvard Medical School, Boston, MA
WE-B-SAN2-1	Fuzzy Inference Based Failure Modes and Effects Analysis (FMEA) for the Acceptance and Commissioning of a Ring-Gantry LINAC J Chang*, S Jang , P Teo , R Lalonde , D Heron , M Huq , UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine, Pittsburgh, PA
WE-C1030-GePD-F2-3	Multitask-Based Supervised Deep Learning Using Contrast-Enhanced CT (CECT) Images for Hepatocellular Carcinoma (HCC) Intrahepatic Progression Risk Analysis L Wei1*, D Owen2 , M Mendiratta-Lala3 , B Rosen2 , K Cuneo2 , T Lawrence2 , R Ten Haken2 , I El Naqa2 , (1) Applied Physics Program, University of Michigan, Ann Arbor, MI, (2) Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, (3) Department of Radiology, University of Michigan, Ann Arbor, MI
WE-C930-GePD-F5-4	Detecting Significant Nodal Volume Shrinkage During Treatment in Head-And-Neck Radiotherapy Using Image Saliency Y Hu*, C Polvorosa , C Tsai , S Fontenla, G Mageras , M Hunt , Memorial Sloan Kettering Cancer Center, New York, NY
WE-C930-GePD-F8-3	Interactive Deep Learning-Based Delineation of Gross Tumor Volume for Post-Operative Glioma Patients M Nordstrom1,2*, J Soderberg2 , N Shusharina3 , D Edmunds3 , F Lofman2 , H Hult1 , A Maki1 , T Bortfeld3 , (1) Royal Institute of Technology, Stockholm, (2) RaySearch Laboratories, Stockholm, (3) Massachusetts General Hospital, Boston
WE-C930-GePD-F9-2	Frequency Dependent Weighting Approach for Megavoltage Multilayer Imagers I Valencia Lozano1*, M Myronakis1, M Shi2,1, P Baturin3, M Lehmann4, R Fueglistaller4 , P Huber4 , D Morf4, D Ferguson1, T Harris1 , M Jacobson1, R Berbeco1, C Williams1, (1) Brigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, USA (2) University of Massachusetts Lowell, Medical Physics Program, Department of Physics and Applied Physics, Lowell, MA, USA (3) Varian Medical Systems, Palo Alto, CA, USA (4) Varian Medical Systems, Baden, Switzerland
WE-FG-301-2	Assessing DNA Damage of Proton Vs. Photon Beams Using Plasmid DNA B Behnke1 , A Giebeler2 , G Mardirossian3 , M Tambasco4 , M Tambasco5*, (1) San Diego State Univ, San Diego, California, (2)California Protons Cancer Therapy Center, San Diego, CA, (3) Genesis Healthcare Partners, Carlsbad, CA, (4) San Diego State Univ, San Diego, CA, (5) San Diego State Univ, San Diego, CA
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-FG-304-10	Creation of An Ultra-Realistic EXtended Multi-Contrast ANthropomorphic (XMAN) Digital Phantom Using Cycle-Generative Adversarial Network (Cycle-GAN) Y Chang1*, F Yin2 , L Ren3 , (1) Duke University Medical Center, Durham, NC, (2) Duke University Medical Center, Durham, NC, (3) Duke University Medical Center, Cary, NC
WE-HI-301-9	Using Knowledge-Based Models to Train Human Planners with Lung and Mediastinum IMRT Planning M Mistro1*, Y Sheng1,2 , Y Ge3 , J Palta4 , J Salama2 , C Kelsey2 , Q Wu1,2 , F Yin1,2 , Q Wu1,2 , (1) Duke University, Durham, NC, (2) Duke University Medical Center, Durham, NC, (3) University of North Carolina at Charlotte, Charlotte, NC, (4) Virginia Commonwealth University, Richmond, VA
WE-J-301-3	Accurate and Instant Prediction of Electron Cutout Factor by An Efficient Residual Neural Network (ResNet) Model C He1 , L Lu2 , T Zhu3 , D Nie4 , S Chang5 , D Shen6 , J Lian7*, (1) Duke University, Durham, ,(2) The University of North Carolina at Chapel Hill, Chapel Hill, NC, (3) Univ of North Carolina at Chapel Hill, Chapel Hill, NC, (4) UNC Chapel Hill, Chapel Hill, ,(5) UNC School of Medicine, Chapel Hill, NC, (6) University of North Carolina at Chapel Hill, Chapel Hill, ,(7) Univ North Carolina, Chapel Hill, NC