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Taxonomy: IM/TH- image Segmentation: MRI
PO-GePV-M-201 | Automatic Segmentation of Rectal Tumor On Magnetic Resonance Images Via A Deep Discriminative Model Consisting of U-Net and Conditional Random Field Based Post-Processing Hao CHEN1*, Xing Li2, X. Sharon Qi3, (1) Xi'an University of Posts and telecommunications, Xian, ,CN, (2) Xi'an University of Posts and Telecommunications, Xian, Shaanxi Province, CN, (3) UCLA School of Medicine, Los Angeles, CA |
PO-GePV-M-248 | Automatic Segmentation of Salivary Glands and Skeletal Muscles for MR-Based Daily Adapted Head and Neck Cancer Radiotherapy C Cardenas1*, T Ermongkonchai2, D Xing3, Z Iqbal1, A Mcdonald1, A Mohamed4, B Harris3, R Khor3, H Bahig5, C Fuller4, S Ng3, (1) The University of Alabama at Birmingham, Birmingham, AL, (2) University Of Melbourne, Melbourne, Australia,(3) Austin Health, Melbourne, Australia, (4) UT MD Anderson Cancer Center, Houston, TX, (5) CHUM |
PO-GePV-M-258 | Inter-Observer and Intra-Observer Variability of Pelvic Organs at Risk Delineation in Multiple Magnetic Resonance Imaging Sequences W Zheng1,2, S Huang1, E Li1,3, J Lian1,4, 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 province, 510060, China, (2) Department of Radiation Oncology, Southern Theater Air Force Hospital of the People's Liberation Army, Guangzhou, Guangdong province, 510050, China, (3) Guangzhou Xinhua College, Guangzhou, Guangdong, 510520, China,(4) Department of Radiation Oncology, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong province, 510405, China |
PO-GePV-T-47 | Evaluate Atlas-Based Auto-Segmentation in MR Images for Liver Yttrium-90 Selective Internal Radiation Therapy J Li*, R Anne, Thomas Jefferson University, Philadelphia, PA |
SU-H400-IePD-F8-1 | Dense UNet for Automatic Contour Correction On Abdominal MRI for MR-Guided Adaptive Radiation Therapy C Sarosiek*, J Ding, A Amjad, Y Zhang, N Dang, X Li, Medical College of Wisconsin, Milwaukee, WI |
SU-H430-IePD-F5-2 | Automated Brain Metastases Segmentation with a Deep Dive Into False Positives Detection H Ziyaee1*, C Cardenas2, D Yeboa1, j Li1, J Johnson1, Z Zhou1, J Sanders1, R Mumme1, L Court1, T Briere1, J Yang1, (1) UT MD Anderson Cancer Center, Houston, TX, (2) The University of Alabama at Birmingham, Birmingham, AL |
WE-B-201-1 | Deep-Learning Based Rectal Tumor Localization and Segmentation On Multi-Parametric MRI Y Zhang1*, S Hu1, L Shi2, X Sun2, N Yue1, K Nie1, (1) Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, (2) Department of Radiation Oncology, Sir Run Run Shaw Hospital, Zhejiang Univ., Hangzhou, CN |
WE-G-BRC-6 | A Deep Learning U-Net Based Model to Automatically Correct Inaccurate Auto-Segmentation for MR-Guided Adaptive Radiotherapy J Ding*, Y Zhang, A Amjad, C Sarosiek, N Dang, X Li, Medical College of Wisconsin, Milwaukee, WI |