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Taxonomy: IM- MRI : Segmentation
| MO-C930-GePD-F2-1 | Evaluation of Different Auto-Segmentation Methods for Prostate Radiotherapy M Cloutier*, S Hsu , L Goddard , A Basavatia , W Tome , Montefiore Medical Center, Bronx, NY |
| MO-C930-GePD-F2-2 | Evaluation of the Auto-Segmentation Based On Self-Registration and Atlas for Cervical Cancer in Adaptive and Replan Radiotherapy Q Zheng1*, J zhang1 , H Zhang2 , J Wang2 , B Gao1 , Y Wang2 , (1) Beijing Geriatric Hospital, Beijing, Beijing, (2) Chinese PLA General Hospital, Beijing, Beijing |
| MO-C930-GePD-F2-4 | Simultaneous Multi-Organ Segmentation Using Multi-Source Adaptive MR Fusion L Zhang1*, F Yin2 , J Cai3 , (1) Duke University Medical Center, Durham, NC, (2) Duke University Medical Center, Durham, NC, (3) The Hong Kong Polytechnic University, Kowloon, Yau Tsim Mong |
| MO-C930-GePD-F2-5 | Testing and Implementation of Atlas Based Segmentation for Radiotherapy Treatment Planning M Jameson*, J Hellyer , C Choong , G Dinsdale , Ingham Institute & Liverpool Cancer Centre, Sydney, NSW |
| MO-E115-GePD-F5-5 | Using Hybrid Convolutional Neural Network to Segment Targets and Organs at Risk for Nasopharyngeal Carcinoma Y Fu*, Y Luo , J Jiang , H Yu , West China Hospital, Chengdu, Sichuan |
| MO-E115-GePD-F9-2 | Evaluation of An Intensity Based Deformable Registration Method for the Generation of Liver Volumes On Post Y90 PET/CT N Lamba*, A Kruzer , S Pirozzi , A Nelson , MIM Software Inc., Cleveland, OH |
| MO-I345-GePD-F6-3 | High Spatial Frequency Structured Light Imaging of Breast Conservation Surgery: Identifiers for Use in Lowering Positive Margin Rates B Maloney1*, D McClatchy1 , W Wells2 , K Paulsen1 , B Pogue1 , (1) Dartmouth College, Hanover, NH, (2) Dartmouth Hitchcock Medical Center, Lebanon, NH |
| MO-K-KDBRC-2 | BEST IN PHYSICS (JOINT IMAGING-THERAPY): Deep Learning Mapping of CT to MRI for Longitudinal Tracking of Lung Tumors for MRI-Guided Radiotherapy J Jiang*, Y Hu , N Tyagi , P Zhang , A Rimner , J Deasy , G Mageras , H Veeraraghavan , Memorial Sloan-Kettering Cancer Center, New York, NY |
| SU-E-KDBRC-6 | A Comparison of Two Deep Learning Architectures to Automatically Define Patient-Specific Beam Apertures C Cardenas1*, B Anderson1 , L Zhang1 , A Jhingran1 , H Simonds2 , J Yang1 , K Brock1 , A Klopp1 , B Beadle3 , L Court1 , K Kisling1 , (1) The University of Texas MD Anderson Cancer Center, Houston, TX (2) Stellenbosch University, Stellenbosch, South Africa (3) Stanford University, Stanford, CA |
| SU-F-205-5 | Med-A-Nets: Segmentation of Multiple Organs in Chest CT Image with Deep Adversarial Networks X Yang1*, J Huang2 , Y Lei3 , S Tian4 , K Higgins5 , J Beitler6 , D Yu7 , X Jiang8 , T Liu9 , W Curran10 , Y Fang11 , (1) Emory University, Atlanta, GA, (2) New York University, New York, NY, (3) Emory University, Atlanta, GA, (4) Emory University, Atlanta, GA, (5) Emory University, Atlanta, GA, (6) Emory University, Atlanta, GA, (7) Emory University, Atlanta, GA, (8) Emory University, Atlanta, GA, (9) Emory Univ, Atlanta, GA, (10) Winship Cancer Institute, Atlanta, GA, (11) New York University, New York, NY |
| SU-H300-GePD-F6-3 | Development of An Automatic Deep Learning Framework for the Detection of Fiducial Markers in Intrafraction Kilovoltage Images A Mylonas1*, P J Keall1, J T Booth2, T Eade2, D T Nguyen1, (1) ACRF Image X Institute, Sydney Medical School, University of Sydney, Camperdown, New South Wales, Australia, (2) Northern Sydney Cancer Centre, Royal North Shore Hospital, St Leonards, New South Wales, Australia |
| SU-H430-GePD-F6-1 | AI-Guided Automated Target Delineation and Planning Optimization by Cloud-Based Treatment Planning System H Zhang1*, R Yang2 , (1) LinkingMed Inc. Beijing, Beijing(2) Peking University Third Hospital, Beijing, Beijing |
| SU-H430-GePD-F9-1 | A Comparison of Interpolation Methods in Head and Neck Radiotherapy Contouring J Spencer1*, K Chen2 , D Boukerroui3 , M Gooding4 , J Fenwick5 , (1) ,,,(2) University of Liverpool, Liverpool, Merseyside, (3) ,,,(4) Mirada Medical Ltd., Oxford, Oxfordshire, (5) Clatterbridge Cancer Centre, Birkenhead, Merseyside |
| SU-I-GPD-E-17 | Consensus Contouring Software with Real-Time Feedback for Radiation Oncology Training J Yang1*, R Fang2 , L Court1 , Z Liao1 , D Gomez1 , J Gunther1 , J Yang1 , (1) UT MD Anderson Cancer Center, Houston, TX, (2) Rice University, Houston, TX |
| SU-I-GPD-J-25 | A Deep Learning Based Auto Segmentation for Lung Tumors On CT Images j Cao*, j wang , m Fan , W Hu , fudan university shanghai cancer center, Shanghai, shanghai |
| SU-I-GPD-J-43 | A MIP-Based 3D Contour Technique for Radiosurgery of Arteriovenous Malformation Y Zhou1*, X Wu2 , W Zhao3 , (1) University of Miami, Coral Gables, Florida, (2) Biophysics Research Institute of America, Aventura, Florida, (3) University of Miami, Coral Gables, Florida |
| SU-I-GPD-J-51 | Interobserver Variations in the Delineation of Target Volumes and Organs at Risk and Their Impact On Dose Distribution in Intensity-Modulated Radiation Therapy for Nasopharyngeal Carcinoma Y Peng*, L Chen , G Shen , J Yao , L Yang , J Li , W Cheng , Y Guan , H Xia , S Liu , X Deng , Sun Yat-sen University Cancer Center, Guangzhou, Guangdong |
| SU-J400-CAMPUS-F2-3 | Evaluation of a Deep Learning Based Thoracic CT Segmentation Algorithm (DLSeg) Q Chen1*, X Feng2 , K Qing3 , T Hunter1 , (1) University of Kentucky, Lexington, KY, (2) Carina Medical LLC, Lexington, KY, (3) University of Virginia, Charlottesville, VA |
| SU-K-KDBRC-4 | Accurate Hippocampus Segmentation Using Fully Convolutional Networks and Deformable Image Registration Based Data Augmentation H Li1*, J Yang2, Y Xiao1, Y Fan1, (1) University of Pennsylvania, Philadelphia, PA, (2) UT MD Anderson Cancer Center, Houston, TX |
| SU-K-KDBRC-6 | A Recursive Ensemble Neutral Network for Organs Segmentation in MR Images for Brain Cancer Radiotherapy H Chen1,2 , X Zhen2 , L Zhou2 , M Chen1 , W Lu1 , S Jiang1 , X Gu1*, (1) UT Southwestern Medical Center, Dallas, TX,(2) Southern Medical University, Guangzhou, Guangdong |
| SU-L-209-2 | Data Integrity Systems for Organ Contours in Radiation Therapy Planning V Shah*, P Lakshminarayanan , J Moore , P Tran , H Quon , C Deville , T McNutt , Johns Hopkins University School of Medicine Department of Radiation Oncology and Molecular Radiation Sciences, Baltimore, Maryland |
| TH-AB-KDBRC-4 | Image Texture Based Fast Contour Validation for Online Adaptive Radiation Replanning Y Zhang1*, Y Hao2 , C Kinchen1 , S Lim1 , X Li3 , (1) Medical College of Wisconsin, Milwaukee, WI, (2) Washington University School of Medicine, St. Louis, MO, (3) Froedtert Hospital and the Medical College of Wisconsin, Milwaukee, WI |
| TH-CD-207-1 | Automatic Organ Segmentation On Head and Neck CT Using 3D Deep Convolutional Neural Network X Feng1*, Q Chen2 , (1) Carina Medical LLC, Lexington, KY, (2) University of Kentucky, Lexington, KY |
| TH-CD-KDBRC-3 | Machine Learning-Based Post-Processing Method for Improved Segmentation of Parotid Glands A Iyer*, S Fontenla , R Haq , H Veeraraghavan , J Oh , J Mechalakos , M Hunt , J Deasy , A Apte , Memorial Sloan-Kettering Cancer Center, New York, NY |
| TH-CD-KDBRC-6 | CT-Based Volumetric Segmentation of Male Pelvis Using Deep Learning A Balagopal*, S Kazemifar , D Nguyen , M Lin , R Hannan , A Owrangi , S Jiang , UT Southwestern Medical Center, Dallas, TX |
| TH-CD-KDBRC-8 | Atrous Convolution and Spatial Pyramid Pooling for More Accurate Tumor Segmentation in MR Images K Men*, P Boimel, J Janopaul-Naylor, H Zhong, M Huang, H Geng, C Cheng, Y Fan, J Plastaras, E Ben-Josef, Y Xiao, University of Pennsylvania, Philadelphia, PA |
| TH-CD-KDBRC-9 | A Deep Learning Based Auto Segmentation for H&N Organs On Treatment Planning CT Images S Sun*, j wang , W Hu , Fudan University Shanghai Cancer Center, Shanghai, Shanghai |
| TH-CD-KDBRC-11 | Deformable Organ Contour Transfer with Deep Inverse Shape Encoding (DISE) Networks for Auto-Segmentation in Low Contrast Regions T Liu1*, X Sun1 , F Yin2 , L Ren2 , (1) Duke University, Durham, NC (2) Duke University Medical Center, Durham, NC |
| TH-EF-KDBRB1-5 | Cardiac Substructure Segmentation and Dosimetry Using a Novel Hybrid MR/CT Cardiac Atlas E Morris1,2*, A Ghanem1,3, M Pantelic1, E Walker1, C Glide-Hurst1,2 (1) Henry Ford Cancer Institute, Detroit, MI (2) Wayne State University, Detroit, MI (3) Alexandria University, Egypt |
| TU-C1000-GePD-F8-1 | Comparison of Automated PET Segmentation Methods in Lymphoma A Weisman1*, T Bradshaw1, Minnie Kieler1 R Jeraj1,2 (1) University of Wisconsin-Madison, Madison, WI, (2) University of Ljubljana, Ljubljana, Slovenia |
| TU-C1030-GePD-F9-1 | Assessment of Respiratory Excursion of Internal Mammary Nodes for ITV Determination M Jermoumi1*, S James1 , C Ferguson1 , J Barrett1 , C Huh1 , A Al-Basheer1 , (1) Georgia Cancer Center, Augusta University, Augusta, GA, |
| TU-C930-GePD-F5-1 | Automatic Segmentation of Vertebrae Using Deep Learning and Generative Adversarial Networks E Boehnke*, A Santhanam , K Sheng , UCLA School of Medicine, Los Angeles, CA |
| TU-C930-GePD-F5-3 | Using Knowledge Based Planning to Determine Whether Geometric Variability in Segmentation Correlates with Dosimetric Variability S Berry1*, C Senra2 , R Haq3 , H Veeraraghavan4 , (1) Memorial Sloan Kettering Cancer Center, New York, NY, (2) Hofstra Northwell School of Medicine, Hempstead, New York, (3) Memorial Sloan-Kettering Cancer Center, New York, NY, (4) Memorial Sloan Kettering Cancer Center, New York, NY |
| TU-C930-GePD-F5-4 | Automated Segmentation of Head and Neck Cancer Patients Using 3D U-Net N Tong1*, S Gou2 , K Sheng3 , (1) Xidian University, Xi'an, Shaanxi,(2) Xidian University, Xi'an, Shaanxi, (3) UCLA School of Medicine, Los Angeles, CA |
| TU-C930-GePD-F5-6 | 3D Ultrasound Prostate Segmentation Using 3D Deeply Supervised V-Net X Yang*, Y Lei , S Tian , T Wang , A Jani , W Curran , P Patel , T Liu , Emory University, Atlanta, GA |
| TU-C930-GePD-F6-2 | DICOM-RT Generator: A Tool for Computational Human Phantoms K Griffin1*, M Mille1 , C Pelletier2 , M Gopalakrishnan3 , J Jung2 , J Kalapurakal3 , C Lee1 (1) Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (2) Department of Physics, East Carolina University, Greenville, NC (3) Department of Radiation Oncology, Northwestern Memorial Hospital, Chicago, IL |
| TU-D-DBRB-5 | Automatic Liver and Tumor Segmentation Using Hierarchical Convolutional-Deconvolutional Neural Networks with Jaccard Distance Y Yuan*, M Buckstein , Y Lo , The Mount Sinai Medical Center, New York, NY |
| TU-E115-GePD-F3-2 | Automatic Delineation of Cardiac Substructures: Analyses From the RadComp Randomized Trial in Breast Cancer J Jung1*, B Ky2, W Kenworthy2, W Bosch3, C Lee4, M Mille5, S MacDonald6, O Cahlon7, J Bekelman8, C Lee5, (1) East Carolina University, Greenville, NC, (2) University of Pennsylvania, Philadelphia, PA, (3) Washington University, Saint Louis, MO, (4) University of Michigan, Ann Arbor, MI, (5) National Cancer Institute, Rockville, MD, (6) Massachusetts General Hospital, Boston, MA, (7) Memorial Sloan-Kettering Cancer Center, New York, NY, (8) University of Pennsylvania, Philadelphia, PA |
| TU-E115-GePD-F6-1 | A Learning-Based MRI Classification for MRI-Only Radiotherapy Treatment Planning Y Lei , H Shu , S Tian , T Wang , A Dhabaan , T Liu , H Shim , H Mao , W Curran , X Yang*, Emory University, Atlanta, GA |
| TU-J430-CAMPUS-F2-3 | Interactive Refinement of Head and Neck Structures Using Multi-Atlas Based Probabilistic Segmentation Maps R Haq*, S Berry , A Iyer , A Apte , M Hunt , J Deasy , H Veeraraghavan , Memorial Sloan-Kettering Cancer Center, New York, NY |
| TU-J430-CAMPUS-F2-4 | Development and Evaluation of a Virtual Reality-Based Radiotherapy Platform J Sutherland*, D La Russa , The Ottawa Hospital, Ottawa, ON |
| TU-K-202-3 | Applying Machine Learning for Automated Liver Segmentation On Radiotherapy Planning CT S Baek1 , Z Sun1*, S Yaddanapudi2 , Y Kim2 , B Gross2 , K Hawkes2 , k McCune2 , T Yuan3 , J Xia2 , (1) University of Iowa, Iowa City, Iowa, (2) University of Iowa Hospitals and Clinics, Iowa City, IA, (3) Affiliated tumor hospital of Guangzhou Medical University, Guangzhou City, Guangdong, China |
| TU-K-DBRB-6 | Robustness of Lung Segmentation On Ultra-Low-Dose Chest CT Using Convolutional Neural Network X Wang*, C Chou , J Hoffman , N Emaminejad , M Wahi-Anwar , M McNitt-Gray , M Brown , David Geffen School of Medicine at UCLA, Los Angeles, CA |
| WE-AB-202-1 | 3D Prostate Segmentation in MR Image Using 3D Deeply Supervised Convolutional Neural Networks X Yang , B Wang*, Y Lei , T Wang , X Jiang , A Jani , H Mao , W Curran , P Patel , T Liu , Emory University, Atlanta, GA |
| WE-C1000-GePD-F6-1 | Automatic Contrast Medium Extraction System Using Monochromatic CT Number D Kawahara1*, S Ozawa2 , S Tanaka3 , K Yokomachi4 , A Saito2 , T Higaki5 , C Fujioka4 , M Tsuneda1 , M Mori1 , Y Ohno4 , Y Nagata2 , (1)Medical and Dental Sciences Course, Graduate School of Biomedical & Health Sciences, Hiroshima University, Hiroshima City 734-8551, Japan, (2)MDepartment of Radiation Oncology, Institute of Biomedical & Health Sciences, Hiroshima University, Hiroshima City 734-8551, Japan, (3) Department of Nuclear Engineering and Management, School of Engineering, University of Tokyo, Tokyo 113-8654, Japan, (4) Radiation Therapy Section, Division of Clinical Support, Hiroshima University Hospital, Hiroshima City 734-8551, Japan, (5) Departments of Diagnostic Radiology and Radiology, Hiroshima University, Hiroshima City 732-0057, Japan |
| WE-C930-GePD-F6-6 | Assessment of the Suitability of the Dice Similarity Coefficient as a Dosimetry Metric Using a Treatment Planning Study in Prostate Cancer D Wang*, W Smith , M Phillips , university Washington, Seattle, WA |