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IM | IM/TH | TH | show all

Taxonomy: IM- MRI : Machine learning, computer vision

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-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
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-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-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-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-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
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-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-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-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-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
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