MENU

Click here to

×

Are you sure ?

Yes, do it No, cancel

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

IM | IM/TH | TH | show all

Taxonomy: IM/TH- Image Analysis (Single Modality or Multi-Modality): Machine learning

MO-E115-GePD-F5-1Convolutional Neural Networks for Identifying Correlation Between Dose Patterns Associated with Poor Survival and Early Local Recurrence After Metastatic Liver SBRT
B Ibragimov1*, Y Yuan3, D Toesca2 , D Chang4 , A Koong5 , L Xing6 , (1) ,,,(2) Stanford University, Stanford, California, (3) Stanford University, Stanford, CA, (4) Stanford University, Stanford, CA, (5) The University of Texas MD Anderson Cancer Center, Houston, TX, (6) Stanford Univ, School of Medicine, Stanford, CA
MO-J430-CAMPUS-F1-3Machine Learning of Tumor Cluster Dosi-Radiomics to Predict Regional Changes On Early-Response FDG PET/CT Imaging of FLARE-RT Protocol Patients
C Duan1,2,4 , W Chaovalitwongse2 , K Puk3 , P Thammasorn2 , S Wang3 , D Hippe4 , L Pierce4 , X Liu2 , J You1 , R Miyaoka4 , H Vesselle4 , P Kinahan4 , R Rengan4 , J Zeng4 , S Bowen4*, (1) Tongji University School of Economics & Management, Yangpu District, Shanghai, (2) University of Arkansas, Fayetteville, AR, (3) University of Texas, Austin, TX, (4) University of Washington School of Medicine, Seattle, WA
MO-K-DBRA-6Spatial, Anatomically-Localized Mapping of Dose-Toxicity Associations Following Prostate Radiotherapy
M Marcello1 , A Kennedy2 , J Dowling3 , A Haworth4 , L Holloway5 , S Gulliford6 , D Dearnaley7 , J Denham8 , M Ebert9*, (1) University of Western Australia, Perth, Western Australia, (2) Sir Charles Gairdner Hospital, Perth, 6009, (3) CSIRO, Brisbane, Queensland, (4) University of Sydney, Sydney, New South Wales, (5) Liverpool and Macarthur cancer therapy centres and ingham Institute, Sydney, NSW, (6) Institute of Cancer Research & Royal Marsden, Sutton, ,(7) Institute for Cancer Research, Sutton, Surrey, (8) University of Newcastle, Newcastle, New South Wales, (9) The University of Western Australia, Nedlands,
MO-K-KDBRC-1Automated Standardization of Organ Labeling in Head and Neck Using Deep Learning
T Rozario*, D Nguyen , M Lin , T Long , M Chen , W Lu , S Jiang , UT Southwestern Medical Center, Dallas, TX
MO-K-KDBRC-3Automated Detection of Vertebral Body Metastases for Fully-Automated Palliative Radiotherapy Using Transfer Learning
T Netherton*, C Cardenas , A Klopp , P Balter , C Chung , C Peterson , R Howell , L Court , The University of Texas MD Anderson Cancer Center, Houston, TX
MO-K-KDBRC-6JACK KROHMER JUNIOR INVESTIGATOR COMPETITION WINNER: Selecting Predictive Genomic Biomarkers for Oropharyngeal Cancer Treatment Prediction by Use of Advanced Machine Learning Method
J Wu1*, C Lian2, S Ruan2, S Mutic1, M Anastasio1, H Gay1, W Thorstad1, X Wang1, H Li1, (1) Washington University in St. Louis, Saint Louis, MO, USA (2) University of Rouen, Rouen, France
SU-F-207-2Deriving Ventilation Imaging From 4DCT by Deep Convolutional Neural Network
Y Zhong1*, Y Vinogradskiy2 , L Chen1 , N Myziuk3 , R Castillo4 , E Castillo3 , T Guerrero3 , S Jiang1 , J Wang1 , (1) UT Southwestern Medical Center, Dallas, TX, (2) University of Colorado Denver, Aurora, CO, (3) Beaumont Health System, Royal Oak, MI, (4) Emory Univ, Atlanta, GA
SU-F-209-3Predicting Motion Compensation Errors for CyberKnife SBRT Liver Patients Using a Machine Learning Algorithm
M Liu1*, D Granville2 , J E Cygler1,2, E Vandervoort1,2 (1) Carleton University, Ottawa, ON (2) The Ottawa Hospital Cancer Centre, Ottawa, ON
SU-F-KDBRA1-6Pancreatic Cancer Risk Prediction Through An Artificial Neural Network
W Muhammad*, G Hart , K Johung , Y Liang , B Nartowt , I Ali , J Deng , Yale university School of Medicine, New Haven, CT
SU-H300-GePD-F9-6Reproducibility 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-H330-GePD-F9-1A Population Based Statistical Model for Dose Distribution in Nasopharynx Cancer
Gang Liu1,2,3 , Xuanfeng Ding2, Zhiyong Yang1, Zhiwen Liang1, Jing Yang1, Xin Nie1, Jun Han1, Hongyuan Liu1, Mi chen1,Ting Cao1, Xiaohui Zhu1, Hong Quan3, Qin Li1* 1. Cancer Center, Union Hospital, Huazhong University of Science and Technology, Tongji Medical College, Wuhan, 430023, China; 2. Beaumont Health System, Royal Oak, MI, 48304, USA. 3. School of Physics and Technology, Wuhan University, Hubei, Wuhan, 430072, China;
SU-H400-GePD-F8-4Radiomics-Based Prediction of Malignant Glioma Grades Using T2-Weighted Magnetic Resonance Images
T Nakamoto1*, W Takahashi1 , A Haga1, 2 , S Takahashi1 , K Nawa1 , T Ohta1 , S Ozaki1 , S Tanaka1 , A Mukasa3 , K Nakagawa1 , (1) The University of Tokyo Hospital (2) Tokushima University (3) Kumamoto University
SU-H430-GePD-F5-6Prediction of Tumor Progression in Locally Advanced Non-Small Cell Lung Cancer Using Standardized Uptake Values From Thoracic PET/CT Images
J M Luna1*, D Kontos1 , K A Cengel1 , C B Simone II 2 , E S Diffenderfer1 , (1) University of Pennsylvania, Philadelphia, Pennsylvania, (2) University of Maryland School of Medicine, Baltimore, Maryland
SU-I-GPD-I-6Impact 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-12Prediction of 3D Dose Distribution and PTV Contour Via Deep Multi-Task Learning Network
F Guo1*, F Kong1 , Y Li2 , L Zhou1 , T Song1 , (1) Southern Medical University, Guangzhou, Guangdong, (2) SUN YAT-SEN UNIVERSITY CANCER CENTER, Guangzhou, Guangdong,
SU-I-GPD-J-55Comparation of Machine Learning Methods for NSCLC Overall Survival Time Prediction Based On Radiomics Analysis
W Sun1*, M Jiang2 , J Dang3 , F Yin4 , (1) School of Information Science and Engineering, Shandong University, Jinan, Shandong, (2) School of Information Science and Engineering, Shandong University, Jinan, Shandong, (3) Chongqing Medical University, Chongqing, Chongqing, (4) Duke University Medical Center, Durham, NC
SU-I-GPD-J-61Transfer Learning-Based Tongue Gestures Classification Using Ultrasound Images
Kele Xu1*, Dawei Feng2 , Shun Zou3 , (1) National University of Defense Technology, Wuhan, Hubei, (2) National University of Defense Technology, Changsha, Hunan, (3) National University of Defense Technology, Wuhan, Hubei
SU-I-GPD-J-67Densely 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-84Using Machine Learning to Predict GI Toxicity in Unresectable Pancreatic Cancer Patients Treated with Stereotactic Body Radiation Therapy
T Wu*, S Liauw , University of Chicago Hospitals, Chicago, IL
SU-K-205-1Convolutional Neural Network Fiducial Detection for Position Reconstruction Using a High-Efficiency Cadmium Tungstate Portal Imager
C Lindsay1*, W Ansbacher1 , I Gagne1 , J Star-Lack2 , M Bazalova-Carter3 , (1) British Columbia Cancer Agency - Vancouver Island Centre, Victoria, BC (2) Varian Medical Systems, Palo Alto, CA, (3) University of Victoria, Victoria, BC
SU-K-205-6Radiomics Characteristics Correlate with Immune Activation: A TCIA/TCGA Data Analysis in Head and Neck Squamous Cell Carcinoma
J Oh1*, E Katsoulakis1 , J Leeman1 , Y Yu2 , J Tsai1 , S McBride1 , N Katabi1 , A Apte1 , N Lee1 , V Hatzoglou1 , N Riaz1 , J Deasy1 , (1) Memorial Sloan Kettering Cancer Center, New York, NY, (2) University of California San Francisco, San Francisco, CA
SU-K-DBRA-4Evaluating the Linearity of Risk Functions Across Radiotherapy Outcomes Using Deep Learning
C Ahern1 , T Pheiffer1*, C Berlind1 , W Lindsay1 , Y Xiao2 , C Simone3 , (1) Oncora Medical, Inc., Philadelphia, PA, (2) University of Pennsylvania, Philadelphia, PA, (3) University of Maryland School of Medicine, Baltimore, Maryland
SU-L-205-2Impact of Image Preprocessing Methods On the Robustness of MRI-Based Radiomic Classifiers for Glioblastoma
H Um*, F Tixier , D Bermudez , A Iyer , A Apte , J Deasy , I Mellinghoff , R Young , H Veeraraghavan , Memorial Sloan-Kettering Cancer Center, New York, NY
SU-L-KDBRC-5MRI-Based Radiomics Distinguishes Treatment Effect From True Progression After Stereotactic Radiosurgery for Brain Metastases
L Peng1 , J Lee1 , K Sheikh1* , P Huang1 , V Parekh1 , B Baker1 , T Kirschbaum1 , F Silvestri1 , J Son1 , A Robinson1 , H Ames1 , J Grimm1 , L Chen1 , C Shen1 , M Soike2 , E McTyre2 , K Redmond1 , M Lim1 , M Jacobs1 , L Kleinberg1 , (1) Johns Hopkins University, Baltimore, MD, (2) Wake Forest School of Medicine, Winston Salem, NC
TH-AB-DBRB-4A Multi-Objective Based Feature Selection Method for Lung Nodule Malignancy Classification
Z Zhou1*, S Li2 , H Hao3 , X Chen4 , M Folkert5 , S Jiang6 , J Wang7 , (1) UT Southwestern Medical Center, Dallas, Texas, (2) Southern Medical University, Guangzhou, Guangdong, (3) Xidian University, Dallas, TX, (4) Xi'an Jiaotong University, Dallas, Texas, (5) UT Southwestern Medical Center, Dallas, Texas, (6) UT Southwestern Medical Center, Dallas, TX, (7) UT Southwestern Medical Center, Dallas, TX
TH-AB-DBRB-8Radio-Morphology: Parametric Shape-Based Features for Outcome Prediction in Radiotherapy
P Lakshminarayanan1*, W Jiang1 , S Robertson2 , Z Cheng1 , P Han1 , M Bowers1 , J Moore1 , J Lee1 , H Quon1 , R Taylor1 , T McNutt1 , (1) Johns Hopkins University, Baltimore, Maryland, (2) WellSpan York Hospital, York, Pennsylvania
TH-AB-KDBRB1-4Deep Learning Based PET Image Noise Reduction Using Both PET and CT Information
X Jin1*, J Fan1 , X Rui2 , (1) GE Healthcare, Waukesha, Wisconsin, (2) GE Global Research Center, Niskayuna, New York
TH-AB-KDBRB1-8A Stacking Method for Predicting Patient QA Passing Rates Using Machine Learning
D Lam*, T Dvergsten , T Zhao , D Yang , S Mutic , B Sun , Washington University in St Louis, St Louis, MO
TH-CD-KDBRC-4Semi-Supervised GANs for Head and Neck Organ Recognition with Small Labeled Datasets
T Rozario*, D Nguyen , M Lin , X Jia , W Lu , S Jiang , UT Southwestern Medical Center, Dallas, TX
TH-CD-KDBRC-12Segmentation of the Prostate and Organs at Risk in Male Pelvic CT Images Using Deep Learning
S Kazemifar*, A Balagopal , D Nguyen , S McGuire , R Hannan , S Jiang , A Owrangi , UT Southwestern Medical Center, Dallas, TX
TH-EF-202-4CBCT Projection-Domain Scatter Correction with a Residual Convolutional Neural Network
Y Nomura1*, Q Xu2 , H Shirato1 , S Shimizu1 , L Xing2 , (1) Hokkaido University, Sapporo, Hokkaido, (2) Stanford University, Palo Alto, CA
TH-EF-202-5Cone-Beam CT Scatter Artifact Removal with Deep Residual Generative Adversarial Network
N Qin1*, Y Gonzalez1 , C Shen1 , C Shieh2 , X Jia1 , (1) University of Texas Southwestern Medical Center, Dallas, TX, (2) The University of Sydney, Sydney, NSW
TH-EF-202-9Noise Subtraction for CT Images Acquired at Multiple Dose Levels Using a Deep Convolutional Neural Network
A Missert*, S Leng , Mayo Clinic, Rochester, MN
TU-C1000-GePD-F1-1Comparison of Gravitational Search Algorithm and Error Back Propagation Algorithm: Applying to CT Ring Artifact Removal Based On Interpolation
Z CHAO*, H Lee , D Kim , H Kim , Yonsei University, Wonju, Gangwon
TU-C1030-GePD-F1-3Comparison 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-F5-5Automatic Localization and Segmentation of the Pancreas in Motion Artifact-Free CBCT Reconstructions Using Fully Convolutional Networks
P Jordan*, A Wang , J Star-Lack , J Van Heteren , Varian Medical Systems, Palo Alto, CA
TU-E115-GePD-F3-1A Machine Learning Process for Delta Radiomics
H Nasief*, X Li , Froedtert Hospital and the Medical College of Wisconsin, Milwaukee, WI
TU-I345-GePD-F9-2Identifying Predictors of Unplanned Hospitalizations After Radiotherapy Using Regularized Survival Models
C Ahern1*, T Pheiffer1 , C Berlind1 , W Lindsay1 , Y Xiao2 , C Simone3 , (1) Oncora Medical, Inc., Philadelphia, PA, (2) University of Pennsylvania, Philadelphia, PA, (3) University of Maryland School of Medicine, Baltimore, Maryland
TU-I345-GePD-F9-5Risk-Index of Colorectal Cancer to Triage for Screening
B. Nartowt*, G. Hart , D. Roffman , I. Ali , W. Muhammad , Y. Liang , J. Deng , Yale university School of Medicine, New Haven, CT
TU-I345-GePD-F9-6Deep Neural Network-Based Modeling of Radiation Pneumonitis Following Lung Stereotactic Body Radiotherapy
S Wang*, A Smith , J Ryckman , M Baine , D Zheng , Y Lei , C Zhang , N Bennion , Q Fan , C Lin , C Enke , S Zhou , University of Nebraska Medical Center, Omaha, NE
TU-K-202-4Automated Segmentation of Malignant Pleural Mesothelioma Tumor On Computed Tomography Scans Using Deep Convolutional Neural Networks
E Gudmundsson1*, C Straus2 , A Nowak3 , H Kindler4 , S Armato5 , (1) ,,,(2) University of Chicago, Chicago, Illinois, (3) University of Western Australia, Crawley, WA, (4) University of Chicago, Chicago, Illinois, (5) The University of Chicago, Chicago, IL
TU-K-202-7Machine Learning On Quality Control of Chest CT Chest Exams: Scan Length Optimization
D Huo*, A Scherzinger , University Colorado Denver, School of Medicine, Aurora, CO
TU-K-207-3Medical Image Annotation with a New Low-Rank Modeling-Based Multi-Label Active Learning Method
J Wu1, S Ruan2 , C Lian2 , S Mutic1 , M Anastasio1 , H Li1* , (1) Washington University in St. Louis, Saint Louis, MO, (2) University of Rouen, Rouen, Normandy
TU-K-207-4Multi-Scale V-Net: A Deep Learning Framework for Brain Tumor Segmentation in Multiparametric MRI
Y Liu*, X Shi , Y Xia , Y Lei , L Tang , T Liu , W Curran , H Mao , X Yang , Emory University, Atlanta, GA
WE-AB-KDBRC-6BEST IN PHYSICS (JOINT IMAGING-THERAPY): Variogram-Weighted Generalized Least Squares Regression to Predict Spatially Variant Tumor Voxel Response On Longitudinal FDG-PET/CT Imaging of FLARE-RT Protocol Patients
D Hippe1 , W Chaovalitwongse2 , C Duan3 , P Thammasorn2 , X Liu2 , R Miyaoka1 , H Vesselle1 , P Kinahan1 , R Rengan1 , J Zeng1 , S Bowen1*, (1) University of Washington School of Medicine, Seattle, WA, (2) University of Arkansas, Fayetteville, AR, (3) Tongji University School of Economics & Management, Yangpu District, Shanghai
WE-C1030-GePD-F4-6Multi-Classification of Clinical Notes for Natural Language Processing-Based Information Aggregation in Radiotherapy
D Ruan*, Y Min , D Low , M Steinberg , UCLA, Los Angeles, CA
WE-C1030-GePD-F7-1A Machine Learning Framework for Predicting the Tumor Control Probability of Radiation Therapy Plans
E Lee1*, Y Cao2 , A Templeton3 , R Yao4 , J Chu5 , (1) Georgia Institute of Technology, Atlanta, GA, (2) Georgia Institute of Technology, Atlanta, GA, (3) Rush University Medical Center, Chicago, IL, (4) Columbus Regional Healthcare, Columbus, GA, (5) Rush University Medical Center, Oak Brook, IL
WE-FG-DBRA-3Ensemble Learning: A Case Study with Knowledge Based Treatment Planning
J Zhang1*, T Xie2 , Y Sheng3 , Q Wu4 , F Yin5 , Y Ge6 , (1) Duke University Medical Center, Durham, NC, (2) Duke University Medical Center, Durham, NC, (3) Duke University Medical Center, Durham, NC, (4) Duke University Medical Center, Durham, NC, (5) Duke University Medical Center, Durham, NC, (6) UNC Charlotte, Charlotte, NC
WE-FG-DBRA-7Modeling of Multiple Planning Target Volumes (PTVs) in Knowledge-Based Planning (KBP)
J Zhang1*, Y Sheng2 , C Wang3 , T Xie4 , F Yin5 , Y Ge6 , Q Wu7 , (1) Duke University Medical Center, Durham, NC, (2) Duke University Medical Center, Durham, NC, (3) Duke University Medical Center, Durham, NC, (4) Duke University Medical Center, Durham, NC, (5) Duke University Medical Center, Durham, NC, (6) UNC Charlotte, Charlotte, NC, (7) Duke University Medical Center, Durham, NC
WE-FG-DBRA-9Performance Comparison of Knowledge-Based Dose Prediction Techniques
A Landers*, R Neph , F Scalzo , D Ruan , K Sheng , UCLA School of Medicine, Los Angeles, CA
WE-J-KDBRA1-1A Method to Detect Errors in Radiation Therapy Physician Orders Using Association Rules
X Chang*, H Li , Y Fu , B Sun , D Yang , Washington University School of Medicine, St Louis, MO
WE-J-KDBRA1-6Statistical Shape Models for the Automated Detection of OAR Segmentation Abnormalities
E Schreibmann*, H Shim , T Liu , N Esiashvili, Emory University, Atlanta, GA