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Taxonomy: IM- PET : Machine learning, computer vision
| MO-J430-CAMPUS-F1-3 | Machine 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-1 | Automated 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-3 | Automated 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-F9-6 | 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-H400-GePD-F8-4 | Radiomics-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-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-L-205-2 | Impact 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-KDBRB1-4 | Deep 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-4 | Semi-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-202-4 | CBCT 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-202-5 | Cone-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-202-9 | Noise 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-F1-1 | Comparison 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-F5-5 | Automatic 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-202-7 | 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-AB-KDBRC-6 | BEST 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 |