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Taxonomy: IM/TH- image segmentation: CT
| MO-AB-221AB-1 | BEST IN PHYSICS (IMAGING): Multiplexed Spectral Computed Tomography (CT) Imaging of Three Contrast Agents C A S Dunning1*, J O'Connell1 , K Murphy1 , S Robinson1 , K Iniewski2 , M Bazalova-Carter1 , (1) University of Victoria, Victoria, BC (2) Redlen Technologies, Saanichton, BC |
| MO-AB-221AB-2 | A KV-MV Cone Beam CT Metal Artifact Reduction Technique Using a Multi-Layer MV Imager and Poly-Energetic Correction M Jacobson1*, M Lehmann2, P Huber2, M Myronakis1, M Shi4, D Ferguson1, I Lozano1, P Baturin3, T Harris1, R Fueglistaller2, C Williams1, D Morf2, R Berbeco1 (1) Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA (2) Varian Medical Systems, Baden-Dattwil, Switzerland (3) Varian Medical Systems, Palo Alto, CA (4) University of Massachusetts, Lowell, Lowell MA |
| MO-AB-221AB-3 | Comparison of a Supervised and An Unsupervised CNN Learning Model for Edge Prediction in Prior Contour Based Total Variation (PCTV) CBCT Reconstruction Y Chen1*, Z Jiang2 , F Yin3 , L Ren4 , (1) Duke University, Durham, NC, (2) Duke Univeristy, Durham, NC, (3) Duke University Medical Center, Durham, NC, (4) Duke University Medical Center, Cary, NC |
| MO-AB-221AB-4 | Improving Low-Dose Cone Beam CT Image Quality Via Convolutional Neural Network N Yuan1,2, S Rao3 , B Dyer3 , S Benedict3 , Y Kang1 , J Qi2 , Y Rong*3 , (1) Northeastern Univerisity, Shenyang (2) Univerisity of California, Davis, Davis, CA (3) UC Davis Cancer Center, Sacramento, CA |
| MO-AB-221AB-5 | Low Dose KV-MV Cone Beam CT with a Multi-Layer MV Imager and Edge-Preserving Sinogram Denoising M Jacobson1*, M Lehmann2, P Huber2, A Wang3, M Myronakis1, M Shi4, D Ferguson1, I Lozano1, Y Hu1, P Baturin3, T Harris1, R Fueglistaller2, J Star-Lack3, C Williams1, D Morf2, R Berbeco1 (1) Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA (2) Varian Medical Systems, Baden-Dattwil, Switzerland (3) Varian Medical Systems, Palo Alto, CA (4) University of Massachusetts, Lowell, Lowell MA |
| MO-AB-221AB-6 | Multi-Energy Element-Resolved Cone Beam CT for Radiotherapy Image Guidance Under Low-Concentration Iodine Contrast Agent H Jung*, C Shen , Y Gonzalez , M Yang , X Jia , University of Texas Southwestern Medical Center, Dallas, TX |
| MO-AB-221AB-9 | Student Beats the Teacher: Deep Learning Using a 3D Convolutional Neural Network (CNN) for Augmentation of CBCT Reconstructed From Under-Sampled Projections Z Jiang*, F Yin , L Ren , Duke University Medical Center, Durham, NC |
| MO-AB-221AB-10 | Experimental Development and Validation of a Rotational Blocker Concept for Under Sample CBCT Reconstruction and Scatter Correction in Radiation Therapy: End to End Confirmation N Hassan Rezaeian1*, Y Xu2 , B Li1 , C Shen1 , L Zhu3 , X Jia1 , (1) The University of Texas Southwestern Medical Ctr, Dallas, TX, (2) Southern Medical University, Guang Zhou, (3) Georgia Institute of Technology, Atlanta, GA, |
| MO-AB-221AB-11 | Accelerated Model-Based Iterative 3D Image Reconstruction Using a Multi-Level Morphological Pyramid A Sisniega1*, J W Stayman1 , S Capostagno1 , C R Weiss1 , T Ehtiati2 , J H Siewerdsen1 , (1) Johns Hopkins University, Balitmore, MD, (2) Siemens Medical Solutions USA |
| MO-C930-GePD-F5-2 | Dual-Energy CT-Based Accurate Stopping Power Mapping Using 3D Deep Convolutional Neural Networks for Head-And-Neck Patients T Wang , Y Lei , J Harms , Y Liu , B Ghavidel*, L Lin , W Curran , J Beitler , T Liu , J Zhou , X Yang , Emory Univ, Atlanta, GA |
| MO-C930-GePD-F5-3 | Improving Differentiation of Tumor and Surrounding Tissues for Tumor Delineation in Pancreas Using Image Textures From Dual-Energy CT D Schott1*, G Noid1 , P Knechtges1 , W Hall1 , B Erickson1 , T Schmidt2 , X Li1 , (1) Medical College of Wisconsin, Milwaukee, WI, (2) Marquette University, Whitefish Bay, WI |
| MO-C930-GePD-F5-6 | The Accuracy of Different Clinical Dual-Energy CT Systems for Proton Therapy Applications E Baer1*, A Warry2, V Rompokos2, G Royle1, A Poynter2, (1) University College London, London (2) University College London Hospital, London |
| MO-C930-GePD-F9-1 | Effective Dose Associated with Routine CT Examinations of the Abdomen and Pelvis with Iodinated Contrast P Patel1*, P Mager2 , L Chang3 , N Gupta4 , (1) Houston Methodist, Sugar Land, TX, (2) ,Houston, ,(3) Houston Methodist, Houston, ,(4) ,Houston, |
| MO-C930-GePD-F9-2 | Evaluation of Dose Distribution by Categories in X-Ray CT Room Using Monte Carlo Simulation T Fujibuchi1*, D Ueno2 , (1) Division of Medical Quantum Radiation Sciences, Department of Health Sciences, Faculty of Medical Sciences, Medical, Kyushu University, Fukuoka, ,(2) Radiation technology course, Department of Health Sciences, Kyushu University,Fukuoka, |
| MO-C930-GePD-F9-3 | Free in Air Correction Factors of Dose Length Product (DLP) of Cone Beam CT Scans A Abuhaimed1*, C Martin2 , (1) King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia,(2) University of Glasgow, Glasgow, UK. |
| MO-C930-GePD-F9-6 | Prediction of Volume CT Dose Index for Dose Modulation with Adaptive Statistical Iterative Reconstruction -V (ASIR-V) Y (Jimmy) Zhou1*, J Nute2 , (1) Cedars-Sinai Medical Center, Los Angeles, CA, (2) UT Health San Antonio, San Antonio, TX |
| MO-E115-GePD-F2-1 | Delta Radiomics: Assessment of Tumor Response for Lung SBRT Patients Using Daily CBCT S Meade1*, G Ge2 , J Molloy3 , D Pokhrel4 , (1) ,Lexington, KY, (2) ,Lexington, KY, (3) Univ Kentucky, Lexington, KY, (4) University of Kentucky, Lexington, KY |
| MO-E115-GePD-F2-5 | Role of Mid-Treatment Imaging Biomarkers in Phase II: Adaptive De-Escalation of Radiation Therapy Dose in HPV-Positive Oropharyngeal Carcinoma (ART) P Galavis*, M Tam , S Kim , E Zan , W Wang , K Hu , NYU Langone Health, New York, NY |
| MO-E115-GePD-F5-2 | Composition of Deformation Vector Fields for Dose Mapping During Head and Neck Adaptive Radiotherapy G Cazoulat*, M McCulloch , H Bahig , B Elgohari , H Elhalawani , A Mohamed , C Fuller , K Brock , The University of Texas MD Anderson Cancer Center, Houston, TX |
| MO-E115-GePD-F5-3 | Respiratory Deformation Registration in 4D-CT/CBCT Using Deep Learning X Teng1*, Y Chen2 , Z Jiang2 , Y Zhao1, L Ren2 , (1) Duke Kunshan University, Kunshan, (2) Duke University, Durham, NC |
| MO-E115-GePD-F5-6 | Investigation of the Accuracy of Deformable Image Registrations Between Average-Intensity Images Y He*, G Cazoulat , M McCulloch , P Balter , Z Liao , R Mohan , K Brock , The University of Texas MD Anderson Cancer Center, Houston, TX |
| MO-E115-GePD-F9-1 | Correction to the Ground Truth Noise From Adjacent Slice Subtractions with the First and Third Generation Adaptive Statistical Iterative Reconstructions Y (Jimmy) Zhou*, A Scott , Cedars-Sinai Medical Center, Los Angeles, CA |
| MO-E115-GePD-F9-2 | Fast Low Contrast Detectability Assessment A Omigbodun*, S Hsieh , University of California Los Angeles, Los Angeles, California |
| MO-E115-GePD-F9-3 | Investigation of Origin and Clinical Impact of Different Artifacts in Thorax CT E Lavdas1*, M Papaioannou2 , A Tsikrika3 , E Pappas4 , G Sakkas5 , V Roka6 , S Kostopoulos7 , S Stathakis8 , N Papanikolaou9 , P Mavroidis10 , (1) University of West Attica, Athens, ,(2) Animus Kyanoys Stavros, Larissa, ,(3) General University Hospital of Larissa, Larissa, ,(4) Animus Kyanoys Stavros, Larissa, ,(5) University of Thessaly, Trikala, ,(6) Health Center of Farkadona, Trikala, ,(7) University of West Attica, Athens, ,(8) University Of Texas Health, San Antonio, TX, (9) University of Texas HSC SA, San Antonio, TX, (10) Univ North Carolina, Chapel Hill, NC |
| MO-E115-GePD-F9-5 | Task-Based Evaluation of a Novel High-Matrix Size Reconstruction Employed to Best Utilize Spatial Resolution in State-Of-The-Art Computed Tomography T Schuermann1*, J Solomon2 , E Samei3 , J Ramirez-Giraldo1 , (1) Siemens Healthineers, Durham, NC, (2) Duke University, Durham, NC, (3) Duke University Medical Center, Durham, NC, (1) Siemens Healthineers, Durham, North Carolina |
| MO-GH-221AB-0 | Computed Tomography-Guided Interventional Procedures F Fintelmann1*, A Jones2*, S Leng3*, K Yang1*, (1) Massachusetts General Hospital, Boston, MA, (2) UT MD Anderson Cancer Center, Houston, TX, (3) Mayo Clinic, Rochester, MN |
| MO-GH-SAN2-4 | Generalized Local Impulse Response Prediction in Model-Based Material Decomposition of Spectral CT W Wang*, M Tivnan , G Gang , S Tilley , J Stayman , Johns Hopkins University, Baltimore, MD |
| MO-I345-GePD-F9-1 | An Apparatus for Measuring Beam Quality in Computed Tomography N Ruiz Gonzalez*, J Lancaster , G Clarke , UT Health Sciences Center, San Antonio, TX |
| MO-I345-GePD-F9-3 | Calcium Score QC Test Tool D Pfeiffer1*, (1) Boulder Community Health, Boulder, CO |
| MO-I345-GePD-F9-6 | Predicting Patient Mis-Centering in CT as a Methodology for Monitoring CT Technologist Performance C Burton*, Harvard University, Boston, MA |
| MO-J430-CAMPUS-F1-2 | CT Radiomics Texture Features Indicate Radiation Induced Pneumonitis T Bejarano*, D Kwon , M De Ornelas , R Yechieli , H Perlow , L Freedman , I Mihaylov , Univ Miami, Miami, FL |
| MO-J430-CAMPUS-F1-3 | Effect of Spectral Pre-Filtration On Organ and Effective Dose in CT Colonography S Lemke1*, D Nachand2 , F Dong2 , A Primak3 , B Herts2 , P Segars4 , X Li2 , (1) Cleveland State University, Cleveland, OH, (2) Imaging Institute, Cleveland Clinic, Cleveland, OH, (3) Siemens Medical Solutions USA, Inc., Cleveland, OH, (4) Duke Univ, Durham, NC |
| MO-J430-CAMPUS-F1-4 | Learning-Based Low Dose CT Reconstruction in Radiation Therapy T Wang , Y Lei , X Dong , Z Tian , Y Liu , X Jiang*, T Liu , W Curran , H Shu , X Yang , Emory Univ, Atlanta, GA |
| MO-J430-CAMPUS-F2-3 | Deep Learning-Based Dual-Energy CT Imaging Using Only a Single-Energy CT Data W Zhao1*, T Lv2 , L Shen3 , X Dai4 , K Cheng5 , M jia6 , y chen7 , L Xing8 , (1) Stanford University, Palo Alto, CA, (2) Southeast University,Nanjing, China,(3) ,Palo Alto, CA, (4) Stanford University, Mountain View, CA, (5) Stanford University, Stanford, CA, (6) ,Palo Alto, CA, (7) Southeast University,Nanjing, China,(8) Stanford Univ School of Medicine, Stanford, CA |
| MO-J430-CAMPUS-F2-5 | Intelligent Synthetic CT Generation Based On CBCT Images Via Unsupervised Deep Learning L Chen*, X Liang , C Shen , S Jiang , J Wang , UT Southwestern Medical Center, Dallas, TX |
| MO-K-SAN1-0 | Advances in Proton and Particle Therapy K Parodi1*, A Lalonde2*, X Ding3*, (1) Ludwig-Maximilians-University Munchen, Garching B. Munich, Germany, (2) Montreal, QC, (3) William Beaumont Hospital, Bloomfield Hills, MI |
| MO-K-SAN1-1 | Advances in ion imaging and range verification K Parodi1*, A Lalonde2*, X Ding3*, (1) Ludwig-Maximilians-University Munchen, Garching B. Munich, Germany, (2) Montreal, QC, (3) William Beaumont Hospital, Bloomfield Hills, MI |
| MO-K-SAN1-2 | Multi-energy CT for dose calculation in particle therapy K Parodi1*, A Lalonde2*, X Ding3*, (1) Ludwig-Maximilians-University Munchen, Garching B. Munich, Germany, (2) Montreal, QC, (3) William Beaumont Hospital, Bloomfield Hills, MI |
| MO-K-SAN1-3 | Spot-scanning Proton Arc therapy: from a concept to reality. K Parodi1*, A Lalonde2*, X Ding3*, (1) Ludwig-Maximilians-University Munchen, Garching B. Munich, Germany, (2) Montreal, QC, (3) William Beaumont Hospital, Bloomfield Hills, MI |
| MO-K-SAN2-1 | Automatic Detection of Contouring Errors Using Convolutional Neural Networks D Rhee1*, C Cardenas2 , H Elhalawani3 , R McCarroll4 , L Zhang5 , J Yang6 , B Beadle7 , L Court8 , (1) MD Anderson Cancer Center, Houston, TX, (2) University of Texas MD Anderson Cancer Center, Houston, TX, (3) UT MD Anderson Cancer Center, Houston, TX, (4) University of Maryland Medical Center, Baltimore, MD, (5) MD Anderson Cancer Center, Houston, TX, (6) MD Anderson Cancer Center, Houston, TX, (7) Stanford University, Stanford, CA, (8) UT MD Anderson Cancer Center, Houston, TX |
| PO-GePV-I-1 | A Comparison of Patient Setup Error On Different Matching Methods Used in X-Ray Volumetric Imaging During Head and Neck VMAT Delivery P Mohandass1,2*, D Khanna2 ,B Nishaanth1,T Thiyagaraj1,C Saravanan1, Narendra Bhalla1, Abhishek Puri1, (1) Fortis Hospital, Mohali, ,(2) Department of Physics, School of Science, Arts, Medica and Management, Karunya Institute of Technology and Science, Coimbatore, TN |
| PO-GePV-I-5 | Use of Virtual Monochromatic Images in a Radiotherapy Clinic A Romano1*, R Tolakanahalli2 , (2) Walker Family Cancer Centre, St. Catharines, ON |
| PO-GePV-I-9 | Unsupervised Classification Routine to Correlate Nonlinearly Related Multiple Images: An Example for CT/CBCT Lung Images Normalization A Chu1*, J Kim2 , Z Xu3 , S Ryu4 , W Liu5 , W Tome6 , (1)(2)(3)(4) Stony Brook University, Stony Brook, NY, (5) Yale Univ. School of Medicine, New Haven, CT, (6) Montefiore Medical Center, Bronx, NY |
| PO-GePV-I-11 | Transfer Learning Based Deformable Image Registration in Pancreatic SBRT C Wessels*, C Rao , N Givehchi , S Scheib , Varian Medical Systems, Baden - Daettwil |
| PO-GePV-I-21 | Comparison of Image Segmentation Algorithms Based On Threshold Technique and Clustering Technique for CT Scan Images M Mahdian Manesh , R Faghihi*, Shiraz universityShiraz |
| PO-GePV-M-1 | Dosimetric Assessment of Three Different Rigid Registration Methods in Proton Therapy for Breast Cancer X Ming1*, Y Sheng1 , Q Zhang1 , J Zhao1 , (1) Shanghai Proton and Heavy Ion Center, Shanghai, |
| PO-GePV-M-7 | Moving Targets in External Versus Internal Motion Tracking R Holla1,2*, D Khanna1 , (1) Department of Physics, Karunya Institute of Technology and Sciences, Coimbatore - 641 114, India, (2) Department of Medical Physics, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India |
| PO-GePV-M-13 | Capsule Architecture Based Automatic Lung Segmentation Strategy Y Liu1*, E Zhang2 ,X Gu3 , (1) Sichuan University, Chengdu, ,(2) The University of Texas Southwestern Medical Ctr, Dallas, TX, ,(3) UT Southwestern Medical Center, Dallas, TX |
| PO-GePV-M-26 | Data Driven Deformable Image Registration for Extreme Deformations E Castillo1*, D Fuentes2 , (1) Beaumont Health Research Institute, Houston, TX, (2) MD Anderson, Houston, TX |
| PO-GePV-P-4 | Computed Tomography Dose Monitoring Systems, Technical Issues for Developers and Technologists H Khosravi1*, A Fatemi1 , P Pike2 , (1) University of Mississippi Medical Center, Jackson, MS, (2) Huntsville Hospital, Huntsville, AL |
| PO-GePV-P-8 | Importance of Vetting Test Equipment After Purchase, Repair Or Calibration: A Case Study P Brunick*, J Wang , B Helbig , J Clements , Kaiser Permanente Southern California Permanente Medical Group, Los Angeles, CA |
| PO-GePV-P-25 | Determination of the Water Equivalent Thickness of Strata XRT Gel and Evaluation of the Dosimetric Effect of Its Application On the Skin of Proton Therapy Patients A Gautam*, S McGovern , X Zhu , N Sahoo , UT MD Anderson Cancer Center, Houston, TX |
| PO-GePV-P-58 | Long-Term Inter-Protocol KV CBCT Image Quality Assessment On the Halcyon Linac Via An Automated QA Approach with the QUART Phantom J Peng1,2,3, H Li3 , E Laugeman3 , T Mazur3 , D Lam3 , T Li4 , B Sun3 , W Hu1,2 , L Dong4 , G Hugo3 , S Mutic3 , B Cai3* , (1) Department of Radiation Oncology, Fundan University Shanghai Cancer Center, Shanghai, China, (2) Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China, (3) Department of Radiation Oncology, Washington University, St. Louis, MO, USA, (4) Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, USA |
| PO-GePV-P-63 | Effect of CT Image Reconstruction Parameters On the Precision of Objective Volume ZY Wang*, CT Wang , J Dong , BX Wen , The First Affiliated Hospital, The Sun Yat-sen UniversityGuangzhou |
| PO-GePV-P-78 | Using Stacked FCN Networks to Improve the Accuracy of Automatic Delineation of Target Volumes and Organs at Risk Y Fu*, H Yu , West China HospitalChengdu |
| PO-GePV-P-95 | Retrospective Computing of Actual Dose Delivered to the Target and Normal Structures in Lung Cancer Patients Treated with SBRT KR MURALIDHAR, P SRINIVAS, M RAMBABU |
| PO-GePV-T-93 | A Novel Approach to Verify the Layer-By-Layer Energy of Scanning Beam Delivery for Proton Therapy j Lah1*, J Son2 , S Moon3 , D Shin4 , (1) Myongji Hospital, Hanyang University College of Medicine,Goyang-si, (2) Seoul National University Hospital, Seoul,(3) Korea University, Seoul,(4) National Cancer Center, Goyang-si, |
| PO-GePV-T-220 | Study On Dose Accumulation in Postoperative IMRT Radiotherapy for Left Breast Cancer After Surgery M Su*1,2, G Gong1 , X Qiu2 , Y Yin1 , (1)Shandong Cancer Hospital Affiliated to Shandong University, Jinan,Shandong (2)University of South China , Hengyang, Hunan |
| PO-GePV-T-254 | An Investigation of Gradient-Based Deformable Registration of CT and CBCT Image C Ma , Y Yin*, Shandong Cancer Hospital Affiliated to Shandong University, Jinan, 37 |
| PO-GePV-T-293 | Target Dose Enhancement by Anatomy-Based Shift (ABS) with 4-D and 6-D Treatment Couch Movement Using Daily Cone Beam CT with Head and Neck Patients S Lee*, B Zhang , H Xu , J Zhou , A Gopal , S Chen , B Yi , University of Maryland School of Medicine, Columbia, MD |
| PO-GePV-T-294 | Dosimetric Impact of Alternative Image Guidance Protocols for Radiation Treatment Setup for Head and Neck Cancer Patients: Daily Cone-Beam Computed Tomography (CBCT) Versus Daily 2D KV Imaging S Lee*, B Zhang , G Lasio , H Xu , A Gopal , S Chen , B Yi , University of Maryland School of Medicine, Baltimore, MD |
| PO-GePV-T-295 | Verification of Setup Accuracy with 6 Degree of Freedom Couch and CBCT T Chen*, H Wang, L Hu, J Zhang, D Barbee, J Xue, NYU Langone Medical Center, New York, NY |
| PO-GePV-T-303 | Predicting Post-SBRT Pulmonary Function Using 4DCT-Derived Ventilation Imaging N Myziuk1*, G Sakthivel2 , L Foster2 , D Solis3 , I Sala 1, E Castillo4 , T Guerrero1,2,4 , (1) William Beaumont Hospital, Dept. of Radiation Oncology, Royal Oak, MI (2) Oakland University William Beaumont School of Medicine, Rochester, MI, (3) Mary Bird Perkins Cancer Center, Baton Rouge, LA (4) Beaumont Health Research Institute, Royal Oak, MI (6) |
| SU-E-225BCD-6 | Residual-Energy Lens Focused Proton Radiography at Clinical Energies: A Monte Carlo Simulation Study M Freeman1*, E Aulwes1 , L Dong2 , T Li2 , P Magnelind1 , F Merrill1 , R Selwyn3 , R Serda3 , R Sidebottom1 , B Teo2 , D Tupa1 , M Espy1 , (1) Los Alamos National Laboratory, Los Alamos, NM, (2) University of Pennsylvania, Philadelphia, PA, (3) University of New Mexico, Albuquerque, NM |
| SU-E-303-2 | Cross-Modality (MR-CT) Educed Deep Learning (CMEDL) for Segmentation of Lung Tumors On CT J Jiang1*, N Tyagi2 , Y Hu3 , A Rimner4 , S Berry5 , J Deasy6 , H Veeraraghavan7 , (1) MSKCC, New York, NY, (2) Memorial Sloan-Kettering Cancer Center, New York, NY, (3) Memorial Sloan Kettering Cancer Center, New York, NY, (4) Memorial Sloan-Kettering Cancer Center, New York, NY, (5) Memorial Sloan Kettering Cancer Center, New York, NY, (6) Memorial Sloan Kettering Cancer Center, New York, NY, (7) Memorial Sloan Kettering Cancer Center, New York, NY |
| SU-E-304-1 | Adaptive Dual Cardiac- and Respiratory-Gated Thoracic Imaging On a Linear Accelerator T Reynolds*, C Shieh , P Keall , R O'Brien, ACRF Image X Institute, University of Sydney, NSW, Australia |
| SU-E-304-2 | Dual Energy CBCT Technique to Produce Virtual Monoenergetic and RED Images Using the On-Board Imager of a Linear Accelerator F Cassetta1*, A Wang2 , R Patel1 , M Haytmyradov1 , J Roeske1 , (1) Loyola University Chicago, Maywood,IL,(2) Stanford University, Stanford, CA |
| SU-E-304-3 | Quantitative Dual-Energy Cone-Beam CT with a Prototype Dual-Layer Flat Panel Detector A Wang1*, L Shi1 , N Bennett1 , E Shapiro2 , A Shiroma2 , J Zhang3 , R Colbeth2 , J Star-Lack2 , M Lu3 , (1) Stanford University, Stanford, CA, (2) Varex Imaging, San Jose, CA, (3) Varex Imaging, Santa Clara, CA |
| SU-E-304-5 | Method and Test Tool for Measurement of 3D MTF Characteristics in Cone-Beam CT P Wu1*, J Boone2 , J Siewerdsen1 , (1) Johns Hopkins Univ, Baltimore, MD, (2) UC Davis Medical Center, Sacramento, CA |
| SU-E-304-6 | Technical Assessment of Dose and 3D Imaging Performance for a New Mobile Isocentric C-Arm for Intraoperative Cone-Beam CT N Sheth1*, T De Silva1 , A Uneri1 , M Ketcha1 , R Han1 , R Vijayan1 , G Kleinszig2 , S Vogt2 , J Siewerdsen1 , (1) Johns Hopkins University, Baltimore, MD, (2) Siemens Healthineers, Erlangen, Germany |
| SU-E-304-7 | The Corgi: A Multi-Purpose Modular Phantom for Dose and Image Quality Assessment in Cone-Beam CT A Uneri1*, A Hernandez2 , G Burkett2 , J Boone2 , J Siewerdsen1 , (1) Johns Hopkins University, Baltimore, MD, (2) University of California-Davis, Sacramento, CA |
| SU-F-221AB-1 | A Patient-Independent CT Intensity Correction Method Using Generative Adversarial Networks (GAN) for Single X-Ray Based Tumor Localization R Wei1*, F Zhou1 , B Liu1 , X Bai1 ,Q Wu2 , (1) Image Processing Center, Beihang University, Beijing, ,(2) Duke University Medical Center, Durham, NC |
| SU-F-221AB-3 | Evaluation of Average Image From During-Treatment 4DCBCT for Lung SBRT Treatment J Liang1*, D Lack2, J Wloch1, D Yan1 , (1) William Beaumont Hospital, Royal Oak, MI, (2) William Beaumont Hospital, Troy, MI |
| SU-F-221AB-5 | Experimental Comparison of Proton CT and Dual Energy X-Ray CT in Terms of Relative Stopping Power Accuracy G Dedes1*, J Dickmann1 , P Wesp1 , R Johnson2 , M Pankuch3 , V Bashkirov4 , R Schulte4 , G Landry1 , K Parodi1 , (1) Ludwig-Maximilians-Universitaet Muenchen, Garching B. Muenchen, Germany,(2) U.C. Santa Cruz, Santa Cruz, CA, (3) Northwestern Medicine Chicago Proton Center, Warrenville, IL, (4) Loma Linda University, Loma Linda, CA, |
| SU-F-221AB-7 | Reconstructing CT Images From Cone-Beam CT Projections Using Learned Primal Dual Reconstruction X Liang*, Y Gonzalez, D Nguyen, Y Zhang, S Jiang, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA |
| SU-F-225BCD-5 | Tumor Phase Recognition by Local Principal Component with Multivariate Singular Spectrum Analysis From Cone-Beam Tomography Projections and External Surrogates P Tsai*, B Lu , G Yan , C Liu , University of Florida, Gainesville, FL |
| SU-F-302-3 | Automated Fiducial-Based Registration and Dose Normalization for 3D Dosimetry Y Wang1*, O Dona2 , Y Xu3, J Adamovics4 , C Wuu5 , (1) Columbia University, New York, NY, (2) Columbia University, New York, NY, (3) Columbia University, New York, NY, (4) HEURIS, INC., Skillman, NJ, (5) Columbia Univ, New York, NY |
| SU-F-304-1 | Fast 4D CBCT Scans: Combining Respiratory Guided Imaging and Advanced Reconstruction Algorithms to Reduce Imaging Time and Dose O Dillon*, R O'Brien , C Shieh , P Keall , University of Sydney, Sydney, NSW |
| SU-F-304-4 | General Simultaneous Motion Estimation and Image Reconstruction (G-SMEIR) for CBCT S Zhou1*, Y Chi1 , J Wang2 , M Jin1 , (1) University of Texas at Arlington, Arlington, TX, (2) UT Southwestern Medical Center, Dallas, TX |
| SU-F-304-6 | Known-Component Metal Artifact Reduction (KC-MAR) for Intraoperative Cone-Beam CT in Spine Surgery: A Clinical Pilot Study X Zhang1*, A Uneri1 , S Doerr1 , J Stayman1 , C Zygourakis2 , S Lo2 , N Theodore2 , J Siewerdsen1 , (1) Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, (2) Department of Neurosurgery, Johns Hopkins Medicine, Baltimore, MD |
| SU-F-304-8 | Accurate CBCT Prostate Segmentation Aided by CBCT-Based Synthetic MRI Y Lei , S Tian , Z Tian , T Wang , Y Liu , X Jiang , T Liu , A Jani , W Curran , P Patel , X Yang*, Emory Univ, Atlanta, GA |
| SU-F-SAN2-1 | CBCT Image Quality Augmentation Using Deep Learning Models: A Comparison Study Y Zhao1*, Z Jiang2 , X Teng1 , L Ren2 , (1) Duke Kunshan University, Kunshan,(2) Duke Univeristy, Durham, NC |
| SU-F-SAN2-2 | AI-Seg: An Artificial Intelligence (AI)-Based Automatic Organs at Risk(OAR) Contouring Platform for Head and Neck Cancer (H&N) Radiotherapy J Wu*, P Lynch , J Shah , W Lu , X Gu , UT Southwestern Medical Center, Dallas, TX |
| SU-F-SAN2-5 | Improving the Robustness of a Deep Learning Based Thoracic CT Segmentation Algorithm (DLSeg) Q Chen1*, X Feng2 , M Bernard1 , (1) University of Kentucky, Lexington, KY, (2) University of Virginia, Charlottesville, VA |
| SU-I300-GePD-F6-3 | Effects of CT Image Acquisition and Reconstruction Parameters On Automatic Contouring Algorithms K Huang*, D Rhee , R Ger , R Layman , J Yang , C Cardenas , L Court , MD Anderson Cancer Center, Houston, TX |
| SU-I300-GePD-F6-4 | Evaluation of Abdominal Autosegmentation Versus Inter-Observer Variability On a High-Speed Ring Gantry CBCT System Philip M. Adamson*, Petr Jordan* , Varian Medical Systems, Palo Alto, CA |
| SU-I300-GePD-F6-6 | Using a Bayesian Neural Network Approximation to Quantify the Uncertainty in Segmentation Prediction On Prostate Cancer D Nguyen*, A Balagopal , C Shen , M Lin , R Hannan , S Jiang , Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, USA |
| SU-I300-GePD-F8-5 | The Feasibility of MVCT-Based Radiomics for Delta-Radiomics in Head and Neck Cancer K Abe1,2*, N Kadoya2 , S Tanaka2 , Y Nakajima1,2 , S Hashimoto1 , T Kajikawa2 , K Karasawa1 , K Jingu2 , (1) Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan,(2) Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendal, Japan |
| SU-I300-GePD-F9-1 | A Dosimetric Evaluation of Daily CBCT Imaging for Prostate Radiotherapy A Gopal*, B Zhang , S Lee , G Lasio , S Chen , B Yi , Univ. of Maryland School Of Medicine, Baltimore, MD |
| SU-I300-GePD-F9-3 | Investigation of Dosimetric Consequence Via Cone-Beam CT Based Dose Reconstruction in Non-Small Cell Lung Cancer Radiotherapy C Ma1 , Y Yin2*, (1) Shandong Cancer Hospital Affiliated to Shandong University, Jinan, 37, (2) ,Jinan, |
| SU-I300-GePD-F9-6 | Optimal CBCT Parameters for SRS Image Guidance E Sudentas*, N Kalach , Mount Sinai West, New York, NY |
| SU-I330-GePD-F5-3 | Evaluating a Model-Based 4DCT Technique for Managing Respiration-Induced Motion of Abdominal Tumors D O'Connell*, M Lauria , J Lewis , A Santhanam , A Raldow , P Lee , D Low , Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA |
| SU-I330-GePD-F6-1 | A Monte-Carlo Study of Proton Radiography of Lung Tumor in Motion W Huo1*, T Zwart2 , J Cooley3 , K Jee4 , G Sharp5 , S Rosenthal6 , X Xu7 , H Lu8 , (1) University of Science and Technology of China, Hefei, ,(2) Mevion Medical Systems, Littleton, MA, (3) Mevion Medical Systems Inc, Littleton, MA, (4) Massachusetts General Hospital, Boston, MA, (5) Massachusetts General Hospital, Boston, MA, (6) Mevion Medical Systems, Inc., Littleton, MA, (7) University of Science and Technology of China, Hefei, ,(8) Massachusetts General Hospital, Boston, MA |
| SU-I330-GePD-F6-4 | On-Board Imaging with High Energy MeV Proton Radiographic Imaging Using a Proton Therapy System G Wright1 , N Alsbou2, S Ahmad1 ,I Ali1 , (1) University of Oklahoma Health Sciences, Oklahoma City, OK, (2) Department of Engineering and Physics, University of Central Oklahoma, Edmond, OK |
| SU-I330-GePD-F9-6 | Pseudo-CBCT Image Prediction of Head and Neck Cancer Patient Using Principal Component Vector Fields of Early Treatment Fractions M Nakano1*, T Imae2 , T Nakamoto2 , A Haga3 , K Nawa2 , Y Nomura2 , R Chhatkuli4 , K Demachi5 , W Takahashi2 , K Yamamoto6 , K Nakagawa2 , M Hashimoto7 , Y Yoshioka1 , M Oguchi1 , (1) Cancer Institute Hospital of JFCR, Tokyo, Japan, (2) Department of Radiology, The University of Tokyo Hospital, Tokyo, Japan, (3) University of Tokushima, Tokushima, Japan, (4) National Institute of Radiological Sciences, Chiba, Japan,(5) Faculty of Engineering, The University of Tokyo, Tokyo, Japan, (6) Department of Radiology, Teikyo University Hospital, Tokyo, Japan, (7) Faculty of Allied Health Sciences, Kitasato University, Sagamihara, Japan |
| SU-I400-GePD-F6-1 | An Experimental Evaluation of Mega-Voltage Fan-Beam CT Using a Linear Accelerator H Gong1*, S Tao1 , J Gagneur2 , W Liu2 , C McCollough1 , Y Hu2 , S Leng1 , (1) Mayo Clinic, Rochester, MN, (2) Mayo Clinic Arizona, Phoenix, AZ |
| SU-I400-GePD-F6-6 | Multi-Institution Analysis of Cone-Beam CT Image Quality Performance N Becker1*, A McNiven1 , L Buckley2 , P Rapley3 , E Sabondjian4 , D Jaffray1 , D Letourneau1 , (1) The Princess Margaret Cancer Centre - University Health Network, Toronto, ON, (2) The Ottawa Hospital Regional Cancer Centre, Ottawa, ON, (3) Thunder Bay Regional Health Sciences Centre, Thunder Bay, ON, (4) Mississauga Halton/Central West Regional Cancer Program - Trillium Health Partners, Mississauga, ON |
| SU-I400-GePD-F9-1 | Accuracy of the Helically-Acquired CTDIvol as An Alternative to Traditional Methodology S Leon1*, R Kobistek2 , Z Zhang3 , E Olguin4 , I Barreto5 , B Schwarz6 , (1) University of Florida, Gainesville, FL, (2) Nat'l Physics Consultants, Ltd, Mentor, OH, (3) University of Florida, Gainesville, FL, (4) University of Florida ,Gainesville, FL, (5) University of Florida, Gainesville, FL, (6) University of Florida, Gainesville, FL |
| SU-I400-GePD-F9-2 | Assessment of Regional Computed Tomography DoseIndices in India Towards Establishing DRL A Saravana Kumar*, R Rajakumar , A Jose , D Balalakshmoji , PSG Institute of Medical Sciences and Research, Coimbatore, TN |
| SU-I400-GePD-F9-4 | Optimization of Various Analytical and Iterative Image Reconstruction Methods M Mahdian Manesh*, R Faghihi , Shiraz universityShiraz |
| SU-I430-GePD-F5-3 | Intrafraction Imaging of the CBCT Simultaneous to VMAT Delivery Provides Patient-Tumor Positioning Verification and Potential for Optimizing Off-Line Adaptive Treatment Planning D Campos1*, A Hernandez2 , D Hernandez3 , S Benedict4 , (1) University of California - Davis, Sacramento, CA, (2) University of California-Davis, Sacramento, CA, (3) Univ of California, Davis, Sacramento, CA, (4) UC Davis Cancer Center, Sacramento, CA |
| SU-I430-GePD-F5-6 | Tumor Tracking and Motion Modeling in SBRT of Abdominal Tumors with Implanted Fiducials Using Pre-Treatment CBCT Projections and Template Matching and Sequential Stereo Triangulation O Oderinde1*, H Mostafavi2 , D Simpson1 , J Murphy1 , L Cervino1 , (1) University of California San Diego, San Diego, CA, (2) ,Palo Alto, CA, |
| SU-I430-GePD-F9-1 | CT Textures in Selection Optimization of HPV-Associated Oropharynx Cancer Patients for Transoral Robotic Surgery T Bejarano*, M Samuels , G Thomas , F Civantos , J Leibowitz , L Freedman , S Samuels , I Mihaylov , Univ Miami, Miami, FL |
| SU-I430-GePD-F9-2 | Development of Multi-Atlas-Based Prostatic Urethra Identification Method Using Machine Learning H Takagi1*, N Kadoya2 , T Kajikawa2 , S Tanaka2 , Y Takayama2 , T Chiba2 , K Ito2 , S Dobashi1 , K Takeda1 , K Jingu2 , (1) Course of Radiological Technology, Health Sciences, Tohoku University Graduate School of Medicine, Sendai, 04, (2) Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, |
| SU-I430-GePD-F9-4 | Quantitative Evaluation of Image Quality in Low Dose CT Images Obtained by Deep Learning D Lee*, H Kim , |
| SU-I430-GePD-F9-5 | Step-Wise Solution to Evaluate CT Radiomic Feature Variability Due to Correlated Noise Texture M Shafiq ul Hassan1*, F Guo1 , H Chen1 , G Zhang2 , E Moros2 , Z Chen1 , (1) Yale New Haven Hospital, New Haven, CT, (2) Moffitt Cancer Center, Tampa, FL, |
| SU-I430-GePD-F9-6 | Subset of Reproducible Radiomic Features as a Function of Multiple CT Imaging Parameters M Shafiq ul Hassan1*, F Guo1 , H Chen3 , G Zhang4 , E Moros5 , Z Chen6 , (1) Yale New Haven Hospital, New Haven, CT, (2) Yale New Haven Hospital, New Haven, CT, (3) Yale New Haven Hospital, New Haven, CT, (4) H. Lee Moffitt Cancer Center, Tampa, FL, (5) H. Lee Moffitt Cancer Center, Tampa, FL, (6) Yale Univ. School of Medicine & YNHH, New Haven, CT |
| SU-K-221AB-2 | On the Quantitative Analysis of Biomechanical Lung Model Consistency Using 5DCT Datasets B Stiehl1*, M Lauria1 , D O'Connell1 , K Hasse2 , I Barjaktarevic1 , P Lee1 , D Low1 , A Santhanam1 , (1) University of California, Los Angeles, Los Angeles, CA, (2) University of California, San Francisco, San Francisco, CA |
| SU-K-221AB-7 | Evaluation of Deformable Image Registration Accuracy in Pediatric Radiotherapy Following TG-132 Recommendations O Ates*, L Zhao , C Hua , T Merchant , St. Jude Childrens Research Hospital, Memphis, TN |
| SU-K-221CD-1 | A Deep-Learning Based Lower-Dose CT Simulation Technique in Image Domain H Gong*, S Leng , C McCollough , L Yu , Mayo Clinic, Rochester, MN |
| SU-K-221CD-2 | Achieving Consistent Tube Output Curves On CT Scanners with Different Implementations of Tube Current Modulation A Ferrero*, C Favazza , K Glazebrook , M Adkins , L Yu , Mayo Clinic, Rochester, MN |
| SU-K-221CD-3 | Exploring the Limits of Size-Specific Dose Estimates (SSDE) as An Estimate of Lung and Breast Dose From Routine Chest CT Examinations A Hardy*, M Bostani , C Cagnon , M McNitt-Gray , University of California, Los Angeles, Los Angeles, CA |
| SU-K-221CD-4 | Simulation of Scatter to Primary Ratio of X-Ray CT Using a Hybrid Stochastic-Deterministic Method R Liu1*, S Zhang2 , J O'Sullivan3 , J Williamson4 , B Whiting5 , T Webb6 , T Zhao7 , (1) Washington Univ. in St. Louis, Saint Louis, MO, (2) Washington University Saint Louis, Saint Louis, ,(3) Washington University, St. Louis, MO, (4) Washington University, Richmond, VA, (5) University of Pittsburgh, Pittsburgh, PA, (6) Washington University, St. Louis, MO, (7) Washington University School of Medicine, St. Louis, MO |
| SU-K-221CD-6 | A Factor of 5 Dose Reduction Using Spectral Shaping On PCD-CT for Ultra-High Resolution Temporal Bone Imaging W Zhou*, K Rajendran , S Tao , B Voss , J Lane , M Carlson , D DeLone , J Fletcher , C McCollough , S Leng , Mayo Clinic, Rochester, MN |
| SU-K-221CD-7 | Impact of Tube Potential On Water Equivalent Diameter and Size Specific Dose Estimate Values for Head, Chest, and Abdomen CT Scans S McCollough*, T Moen , J Schneider , T Vrieze , S Leng , C McCollough , Mayo Clinic, Rochester, MN |
| SU-K-303-7 | Projection-Domain Convolutional Neural Network Denoising for X-Ray Phase-Contrast Micro Computed Tomography E Shanblatt*, A Missert , B Nelson , S Leng , C McCollough , Mayo Clinic, Rochester, MN |
| SU-L-221AB-3 | High-Resolution Inhale/Exhale CT Parametric Response Mapping for Assessment of Pulmonary Dysfunction in Non-Small Cell Lung Cancer Patients Undergoing Radiation Treatment D Owen*, A Fortuna , B Hoff , S Jolly , R Ten Haken , C Galban , M Matuszak , University of Michigan, Ann Arbor, MI |
| SU-L-221CD-1 | 3D-Printed Textured Phantoms for Assessment of High Resolution CT J Li*, G Gang , M Brehler , H Shi , J Stayman , Johns Hopkins University, Baltimore, MD |
| SU-L-221CD-2 | Evaluation of Deformable Image Registration Accuracy and Its Impact On Dual-Energy CT Images J Huang*, C Matrosic , M Lawless , L Di Maso , J Miller , University of Wisconsin, Madison, WI |
| SU-L-221CD-3 | Experimental Assessment of Dual-Energy CT Estimation Bias Reduction with Joint Statistical Image Reconstruction in Sinogram Domain-Based Material Decomposition J Lu1 , S Zhang2 , J Williamson3 , T Webb4 , D Politte5 , B Whiting6 , J O'Sullivan7*, (1) Washington University, St. Louis, MO, (2) Washington University, St. Louis, MO,(3) Washington University, St. Louis, MO, (4) Washington University, St. Louis, MO, (5) Washington University, St. Louis, MO,(6) University of Pittsburgh, Pittsburgh, PA, (7) Washington University, St. Louis, MO |
| SU-L-221CD-4 | Feasibility of Different Prognostic Prediction Models for Lung Cancer Stages I-IIIB Based On Radiomic Signatures K Ninomiya*, H Arimura , Kyushu UniversityFukuoka |
| SU-L-221CD-5 | High-Resolution Spectral Micro-CT: System Design, Reconstruction Method and Preliminary Results Q Wang1*, Y Zhu2 , S Deng2 , H Zhang2 , H Yu1 , (1) University of Massachusetts Lowell, Lowell, MA, (2) Capital Normal University, Beijing |
| SU-L-221CD-6 | Multiple Resolution Residual Network for Automatic Lung Tumor and Lymph Node Segmentation Using CT Images H Um*, J Jiang , A Rimner , L Luo , J Deasy , M Thor , H Veeraraghavan , Memorial Sloan Kettering Cancer Center, New York, NY |
| SU-L-221CD-7 | Reconstruction of Difference with Anatomical Change Preserving Deformable Registration for Sequential Lung Cancer Screening J Flores1*, G Gang2 , C Lin3 , S Fung4 , J Stayman5 , (1) Johns Hopkins University, Baltimore, MD, (2) Johns Hopkins University, Baltimore, MD, (3) Johns Hopkins University Radiology, Baltimore, ,(4) Siemens Healthineers, Ellicott City, MD, (5) Johns Hopkins University, Baltimore, MD |
| SU-L-221CD-8 | Respiratory Motion Characterization and Motion Artefact Reduction Using Volumetric 4-Dimensional Computed Tomography H Young1,2,3*, T Lee1,2 , S Gaede1,3 , (1) Western University, London, ON, (2) Robarts Research Institute, London, ,(3) London Regional Cancer Program, London, ON |
| SU-L-225BCD-3 | An Independent Evaluation of a Deep Learning Research Tool for Autocontouring CT Images of Prostate Radiotherapy Patients D Granville1*, B Wilson1 , J Sutherland1,2 , D La Russa1,2 , M MacPherson1,2,3 , (1) The Ottawa Hospital, Ottawa, ON, (2) University of Ottawa, Ottawa, ON, (3) Carleton University, Ottawa, ON |
| SU-L-225BCD-7 | Learning-Based Automatic Segmentation of Arteriovenous Malformations On Contrast CT Images in Brain Stereotactic Radiosurgery T Wang*, Y Lei , S Tian , X Dong , X Jiang , J Zhou , T Liu , S Dresser , W Curran , H Shu , X Yang , Emory Univ, Atlanta, GA |
| TH-A-221AB-2 | A Flexible Iterative Reconstruction Framework for Low Dose CT Q Lyu*, D Ruan , J Hoffman , R Neph , M McNitt-Gray , K Sheng , UCLA School of Medicine, Los Angeles, CA |
| TH-A-221AB-3 | Quantitative Prior-Image-Based CT Reconstruction with Mismatched Prior H Zhang1*, D Capaldi2 , D Zeng3 , J Ma4 , L Xing5 , (1) Stanford University, Stanford, CA, (2) Stanford University, Stanford, California, (3) Southern Medical University, Guangzhou, ,(4) Southern Medical University, Guangzhou, ,(5) Stanford University, Stanford, CA |
| TH-A-221AB-4 | Noise Reduction in CT Image Using Prior Knowledge Aware Iterative Denoising S Tao*, K Rajendran , W Zhou , C McCollough , S Leng , Mayo Clinic, Rochester, MN |
| TH-A-221AB-5 | Dependence of Scatter-To-Primary Ratio On X-Ray Energy B Whiting1*, J Williamson2 , R Liu3 , T Webb4 , M Porras-Chaverri5 , J O'Sullivan6 , (1) University of Pittsburgh, Pittsburgh, PA, (2) Washington University, Richmond, VA, (3) Washington Univ. in St. Louis, Saint Louis, MO, (4) Washington University, St. Louis, MO, (5) Universidad de Costa Rica, San Jose, SJ, (6) Washington University, St. Louis, MO |
| TH-A-221AB-6 | Effect of Multi-Slit Collimator Motion On SparseCT Image Quality for Low-Dose CT Examinations B Chen1*, E Kobler2 , T Allmendinger3 , A Sodickson4 , D Sodickson5 , R Otazo6 , (1) NYU School of Medicine, New York, NY, (2) Graz University of Technology, Graz, ,(3) Siemens Healthineers, Forchheim, ,(4) Brigham and Women's Hospital, Boston, MA, (5) NYU School of Medicine, New York, NY, (6) Memorial Sloan Kettering Cancer Center, New York, NY |
| TH-A-221AB-8 | Non-Rigid 4D-CT Image Registration Using An Unsupervised Deep Convolutional Neural Network Y Lei*, Y Liu , T Wang , Z Tian , S Tian , W Curran , T Liu , K Higgins , X Yang , Emory Univ, Atlanta, GA |
| TH-A-221AB-9 | Respiratory Adaptive Computed Tomography (REACT) Reduces 4DCT Imaging Artifacts Through Prospective Gating: First Experimental Results N Morton1*, J Sykes2 , J Barber2 , C Hofmann3 , P Keall1 , R O'Brien1 , (1) University of Sydney, Sydney, , (2) Blacktown Hospital, Blacktown, ,(3) Advanced Therapies, Siemens Healthcare GmbH, Forchheim, , |
| TH-A-221AB-10 | Impact of Radiation Dose On Quantification Accuracy of Penumbra and Infarct Core Volume in CT Brain Perfusion J Browne*, M Bruesewitz , T Vrieze , E Lindell , C McCollough , L Yu , Mayo Clinic, Rochester, MN |
| TH-A-225BCD-3 | A Novel Deformable Registration Method Using a Multi-Scale Framework with Joint Training of Unsupervised Deep Learning Models Z Jiang*, F Yin, L Ren, Duke University Medical Center, Durham, NC |
| TH-A-SAN2-7 | Deep-Learning Based CBCT Image Correction for CBCT-Guided Adaptive Radiation Therapy J Harms1*, Y Lei1 , T Wang1 , R Zhang1 , J Zhou1 , X Dong1 , P Patel1 , K Higgins1 , X Tang2 , W Curran1 , T Liu1 , X Yang1 , (1) Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, (2) Department of Radiology and Imaging Sciences and Winship Cancer Institute, Emory University, Atlanta, GA 30322 |
| TH-BC-304-1 | BEST IN PHYSICS (IMAGING): Reference Dataset for Benchmarking Organ Doses Derived From Monte Carlo Simulations of CT Exams A Hardy1*, M Bostani1 , E Angel2 , C Cagnon1 , M McNitt-Gray1 , (1) UCLA, Los Angeles, CA, (2) Canon Medical Systems, Tustin, CA |
| TH-BC-304-3 | Fetal Dose Estimates for Tube Current Modulated (TCM) and Fixed Tube Current (FTC) Abdominal/Pelvic CT Examinations of Pregnant Patients A Hardy1*, M Bostani1 , E Angel2 , C Cagnon1 , M McNitt-Gray1 , (1) UCLA, Los Angeles, CA, (2) Canon Medical Systems, Tustin, CA |
| TH-BC-304-4 | Modeling CT Scanner Complexities Using Deterministic Linear Boltzmann Transport Equation Solver for Patient-Specific CT Dose Estimation S Principi1,2*, A Wang3 , A Maslowski4 , T Wareing4 , P Jordan4 , T Schmidt1,2 , (1) Medical College of Wisconsin, Milwaukee, WI, (2) Marquette University, Milwaukee, WI, (3) Stanford University, Stanford, CA, (4) Varian, Palo Alto, CA |
| TH-BC-304-5 | Multi-Organ Segmentation of CT Images Using Deep-Learning for Instant and Patient-Specific Dose Reporting Z Peng1,2 , X Fang1 , H Shan1 , T Liu1 , X Pei2 , P Yan1 , G Wang1 , B Liu3 , M Kalra3 X G Xu1,2*, (1) Rensselaer Polytechnic Institute, (2) University of Science and Technology of China (3) Massachusetts General Hospital |
| TH-BC-304-6 | A Comparison of the Approach-To-Equilibrium Function Measured On CT Scanners From Four Different Manufacturers Using the ICRU/AAPM CT Radiation Dosimetry Phantom J Steiner*, D Bakalyar , Henry Ford Health System, Detroit, MI |
| TH-BC-304-7 | Direct Measurements of Dynamic Beam Collimation From Four Modern Wide-Beam CT Scanners K Yang*, Z Li , X Li , B Liu , Massachusetts General Hospital, Boston, MA |
| TU-AB-221AB-1 | 3D X-Ray-Induced Acoustic Computed Tomography (3D XACT) S Wang*, P Samant , E Robertson , H Liu , L Xiang , University of Oklahoma, Norman, OK |
| TU-AB-221AB-2 | An Integrated Mass Conservation Formulation for Robust Intensity-Based Computed Tomography (CT) Ventilation E Castillo1*, Y Vinogradskiy2 , R Castillo3 , (1) Beaumont Health Research Institute, Houston, TX, (2) University of Colorado Denver, Aurora, CO, (3) Emory Univ, Atlanta, GA |
| TU-AB-SAN2-6 | A General Framework of Delta-Radiomics for Treatment Response Prediction H Nasief*, X Li , Medical College of Wisconsin, Milwaukee, WI |
| TU-AB-SAN2-7 | Development and Validation of Deep Learning Segmentation Network for Cardio-Pulmonary Substructure Segmentation R Haq*, A Hotca-Cho , A Apte , A Rimner , J Deasy , M Thor , Memorial Sloan Kettering Cancer Center, New York, NY |
| TU-AB-SAN2-8 | Intratumoral and Peritumoral CT Radiomic Modeling to Predict Treatment Failure of Early Stage Non-Small Cell Lung Cancers K Lafata1*, Y Gao2 , Y Chang3 , C Wang4 , C Kelsey5 , F Yin6 , (1) Duke University Medical Center, Durham, NC, (2) Duke University Medical Physics Graduate Program, Durham, NC, (3) Duke University Medical Center, Durham, NC, (4) Duke University Medical Center, Durham, NC, (5) Duke University, Durham, ,(6) Duke University Medical Center, Durham, NC |
| TU-AB-SAN2-12 | Identifying Oropharyngeal Clinical Target Volumes Delineation Patterns From Peer-Reviewed Clinical Delineations Via Cascade 3D Fully-Convolutional Networks C Cardenas1*, J Yang1 , A Mohamed1 , C Fuller1 , B Beadle2 , A Garden1 , L Court1 , (1) University of Texas MD Anderson Cancer Center, Houston, TX, (2) Stanford University, Stanford, CA |
| TU-C1000-GePD-F6-1 | A Deep Sequential Learning Architecture for Xerostomia Prediction in Parotid Glands Using CBCT and Rigid-Registered Dose Images H Tseng1*, B Rosen2, JT Chien3, M Mierzwa4, R Ten Haken5, I El Naqa6 , (1) University of Michigan, Ann Arbor, Ann Arbor, MI, (2) University of Michigan, Ann Arbor, MI, (3)National Chiao Tung University, Hsinchu, Taiwan (4) University of Michigan, Ann Arbor, MI, (5)University of Michigan, Ann Arbor, MI, (6)University of Michigan, Ann Arbor, MI |
| TU-C1000-GePD-F9-2 | Correction Using Image Processing Algorithm for Cone Beam CT Images in Stereotactic Body Radiotherapy (SBRT) R Srivastava1*, S Gaur2 , P Sharma3 , M Sharma4 , D Chauhan5 , N Sehgal6 , J Maria Das7 , m Jayanand8 , (1) International Oncology Centre,Fortis Hospital, Noida, UP, (2) International Oncology Centre,Fortis Hospital, Noida, ,(3) International Oncology Centre,Fortis Hospital, Noida, ,(4) International Oncology Centre,Fortis Hospital, Noida, ,(5) International Oncology Centre,Fortis Hospital, Noida, ,(6) International Oncology Centre,Fortis Hospital, Noida, ,(7) Sanjay Gandhi PG Inst Med Scienes, Lucknow, ,(8) Shobhit University, Merrut, |
| TU-C1030-GePD-F5-2 | Development of a Centralized Motion Prediction Model for Motion Management in Radiation Therapy J Kim*, A Tai , X Li , H Zhong , Medical College of Wisconsin, Milwaukee, WI |
| TU-C1030-GePD-F6-1 | A Methodology for Computer-Aided Diagnosis of Thyroid Lesions Based On Computed Tomography Images C Liu*, Y Yang , D Shao , W Peng , Y Wang , Y Wang , Cancer Institute Hospital, CAMS, Warren, NJ |
| TU-C1030-GePD-F9-1 | A Statistically Characterized Reference Data Set for Image Registration of Pelvis Using Combinatorial Affine Registration Optimization A Yorke1*, I Sala2 , D Solis3 , T Guerrero4 , (1) William Beaumont Hospital, Royal Oak, MI, (2) Beaumont Hospital, Royal Oak, MI, (3) William Beaumont Hospital, Warren, MI, (4) ,Royal Oak, MI |
| TU-C1030-GePD-F9-2 | Application of 4DCT and Enhanced CT Image Deformation Registration in the Determination of Non-Small Cell Lung Cancer Radiotherapy Target C Ma1 , Y Yin2*, (1) Shandong Cancer Hospital Affiliated to Shandong University, Jinan, 37, (2) ,Jinan, |
| TU-C1030-GePD-F9-5 | Intrinsic Measurement of Cardiorespiratory Signals of Centrally-Located Tumour Motion From Thoracic Cone-Beam CT S J Blake*, N Hindley, C-C Shieh, P Keall, R O'Brien, ACRF Image-X Institute, University of Sydney, Sydney, NSW, Australia |
| TU-C1030-GePD-F9-6 | What Image Features Are Good for Correlation-Based Tracking Algorithms Used for Soft Tissue Monitoring in X-Ray Imaging A Jeung*, L Zhu , H Mostafavi , J van Heteren , Varian Medical Systems, Palo Alto, CA |
| TU-C930-GePD-F4-6 | Development of a 3D-Printed Deformable Prostate Insert for a Novel Pelvic End-To-End (PETE) Phantom to Benchmark Adaptive Radiation Therapy C Miller1,2*, J Mourad2, S Foley2, K Labash2, B Brichacek2, J Cunningham1, C Glide-Hurst1,3, (1) Department of Radiation Oncology, Henry Ford Cancer Institute, Detroit, MI, (2) Department of Biomedical Engineering, Wayne State University, Detroit, MI, (3) Department of Radiation Oncology, Wayne State University, Detroit, MI |
| TU-C930-GePD-F6-1 | Generalized Image Quality Analysis for Nonlinear Algorithms in CT G Gang*, X Guo , J Stayman , Johns Hopkins University, Baltimore, MD |
| TU-C930-GePD-F6-6 | Understanding the Impact of Heterogeneous Iterative Reconstruction and Dose Conditions in Low-Dose CT Computer-Aided Detection of Lung Nodules M Wahi-Anwar*, N Emaminejad , G Kim , M McNitt-Gray , M Brown , David Geffen School of Medicine at UCLA, Los Angeles, CA |
| TU-C930-GePD-F9-1 | Automatic Segmentation On CBCT Images Using a Combination of CBCT Enhancement and Deep Learning CT Segmentation S Andersson*, R Nilsson, RaySearch Laboratories AB, Stockholm |
| TU-C930-GePD-F9-2 | Calibrator Recognition of Cone-Beam Image for Geometric Correction Q Ling1*, X Duan2 , J Ma3 , J Huang4 , S Huang5 , J Cai6 , L Zhou7 , Y Xu8 ,(3) UT Southwestern Medical Center, Dallas, TX, (1-2,4-8) Southern Medical University,Guangzhou |
| TU-C930-GePD-F9-3 | Fast CBCT Scatter Estimation Based On Monte Carlo and U-Net A Zhong1*, Y Zhang1 , B Li2 , Z Tian3 , X Jia4 , L Zhou1 , Y Xu1 , X Zhen1 , (1) Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, (2)Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, (3) Emory University, Decatur, GA, (4) The University of Texas Southwestern Medical Ctr, Dallas, TX |
| TU-C930-GePD-F9-4 | Hounsfield Unit Correction of Prostate CBCT Using Cycle-Consistent Generative Adversarial Networks (CycleGAN) O Dona*, Y Wang , A Xu , C Wuu , Columbia Univ, New York, NY |
| TU-C930-GePD-F9-5 | Transfer Learning of a Convolutional Neural Network for CBCT Projection-Domain Scatter Correction with Different Scan Conditions Y Nomura1*, Q Xu2,3 , H Shirato2,4 , S Shimizu2,5 , L Xing2,6 , (1) Department of Radiation Oncology, Graduate School of Medicine, Hokkaido University, Sapporo, Japan, (2) Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education (GI-CoRE), Hokkaido University, Sapporo, Japan, (3) Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China, (4) Department of Radiation Medicine, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan, (5) Department of Radiation Medical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo, Japan, (6) Department of Radiation Oncology, Stanford University, Stanford, CA |
| TU-E-221AB-5 | Anatomically-Specified Conformation Breast CT P Ghazi*, MALCOVA LLC, Baltimore, MD |
| TU-E-SAN2-1 | A Novel Training Strategy for Data with Incomplete Labeling in CNN-Based Head-And-Neck OAR Segmentation X Feng1*, K Qing2 , Q Chen3 , (1) University of Virginia, Charlottesville, VA, (2) Rutgers Cancer Institute of New Jersey, Bridgewater, NJ, (3) University of Kentucky, Lexington, KY |
| TU-E-SAN2-3 | Development of a Fast, Multi-Stage U-Net for Automatic Segmentation of Cardiac Substructures in Non-Contrast CT Images H Lin1*, J Zou1 , T Li1 , B Ky1 , J Bekelman1 , W Bosch2 , H Lu1 , W Kenworthy1 , B Teo1 , L Dong1 , (1) University of Pennsylvania, Philadelphia, PA, (2) Washington Univ, Saint Louis, MO |
| TU-E-SAN2-4 | Development of A Novel Mixing 2D-3D Fully Convolutional Neural Network for Pancreas Segmentation B Ye1 , X Qi2 , S Tan1* (1) Huazhong University of Science & Technology, Wuhan, China (2) UCLA School of Medicine, Los Angeles, CA |
| TU-E-SAN2-5 | Fully Automated Segmentation of 33 Abdominal Structures Using Deep Learning - Implications for Radiotherapy Dose Estimation A Weston*, P Korfiatis , K Philbrick , P Kostandy , A Zeinoddini , A Boonrod , N Takahashi, M Moynagh , B Erickson , Mayo Clinic, Rochester, MN |
| TU-E-SAN2-7 | Modified U-Net for High-Resolution High-Level Feature Extraction and Its Application to Liver-Tumor Segmentation H Seo1*, C Huang2 , L Xing1 , (1) Stanford Univ School of Medicine, Stanford, CA, (2) Stanford Univ School of Engineering and Medicine, Stanford, CA |
| TU-F115-GePD-F2-5 | Radiation Dose Response Model for Ventilation Change Using All Phases of 4DCT E Wallat1*, M Flakus1 , A Wuschner1 , W Shao2 , S Gerard2 , T Patton3 , G Christensen2 , J Reinhardt2 , A Baschnagel1 , J Bayouth1 , (1) University of Wisconsin-Madison, Madison, WI, (2) University of Iowa, Iowa City, IA,(3) University of Denver, Denver, CO |
| TU-F115-GePD-F5-1 | Artificial Intelligence-Based Dose-Guided Patient Positioning for Prostate Cancer Online Adaptive Radiotherapy X Zhang1*, (1) West China hospital of Sichuan university, Chengdu, Sichuan |
| TU-F115-GePD-F5-2 | Commissioning Varians SmartAdapt for Clinical Applications in Adaptive Radiation Therapy J Vickress1,2*, H Afsharpour1 , A Rangel1 , (1) Carlo Fidani Peel Regional Cancer Centre, Trillium Health Partners, Mississauga, ON, (2) Department of Radiation Oncology, University of Toronto, Toronto, CA |
| TU-F115-GePD-F6-1 | Clinical Evaluation and Implementation of a Commercial Iterative CBCT Algorithm Y Zheng*, J Wong , Atlantic Health System, Morristown, NJ |
| TU-F115-GePD-F6-2 | Imaging Quality of Intrafraction 4D CBCT for Lung SBRT Using Flattening Filter-Free Beams: A Phantom Study J Kim*, J Kim , K Keum , H Lee , |
| TU-F115-GePD-F6-4 | Dependence of Radiomics Features On CT Image Acquisition and Reconstruction Parameters Using a Cadaveric Human Liver I Gertsenshteyn1*, J Foy1 , A Crofton2 , V Grekoski3 , T Tran3 , K Guruvadoo3 , H Al-Hallaq1 , S Armato1 , W Sensakovic3 , (1) The University of Chicago, Chicago, IL, (2) Adventist University of Health Sciences, Orlando, FL, (3) Florida Hospital, Orlando, FL |
| TU-F115-GePD-F9-2 | Comparing Profile-Based KV Assist On Revolution Apex to Previous Generation of KV Assist On Revolution CT F Rupcich1*, H Litt2 , (1) GE Healthcare, Waukesha, WI, (2) Perelman School of Medicine of the University of Pennsylvania, Philadelphia, PA |
| TU-F115-GePD-F9-3 | Fat Fraction Based Segmentation of CT Image Based On Surfactant-Free Microemulsion Reference Phantom: A Feasibility Study H Cho1, C Lee1 , B Ahn1 , C Hong2* , (1) Korea Research Institute of Standards and Science,Daejeon, Korea (2) Daegu Catholic University, Daegu,Korea |
| TU-F115-GePD-F9-4 | Human Visual Properties Based Grayscale Contrast Enhancement W Zhou1*, Y Tian1 , (1) Shanghai Siemens Medical Equipment Ltd, Shanghai, |
| TU-F115-GePD-F9-5 | Spatial and Temporal Analysis of Iodine Uptake in the Lungs of a Swine Model M Lawless*, J Miller , J Huang , K Mittauer , A Wuschner , M Flakus , J Meudt , D Shanmuganayagam , J Bayouth , University of Wisconsin-Madison, Madison, WI |
| TU-G-TOUR-I-0 | Brain CT Perfusion K Little*, Ohio State University, Columbus, OH |
| TU-HI-221CD-0 | Patient Dose Monitoring in CT with Tube Current Modulation and Multiple Series J Boone1*, R Dixon2*, B Li3*, D Zhang4*, X Li5*, (1) UC Davis Medical Center, Sacramento, CA, (2) Wake Forest Univ, Winston Salem, NC, (3) Boston University Medical Center, Boston, MA, (4) Harvard, Beth Israel Deaconess Medical Center, Sharon, MA, (5) Massachusetts General Hospital, Belmont, MA |
| TU-HI-SAN2-1 | A Novel Semantic CT Segmentation Algorithm Using Boosted Attention-Aware Convolutional Neural Networks V Kearney*, J Chan , T Wang , A Perry , S Yom , T Solberg , UCSF Comprehensive Cancer Center, San Francisco, CA |
| TU-HI-SAN2-6 | Delta-Radiomics and Tumor Characteristic Factors as a Combined Biomarker for Chemoradiation Therapy of Locally Advanced Pancreatic Cancer H Nasief1*, W Hall2 , C Zheng3 , S Tsai4 , L Wang5 , B Erickson6 , X Li7 , (1) Medical College of Wisconsin, Marshall, WI, (2) Medical College of Wisconsin, Milwaukee, WI, (3) University of Wisconsin Milwaukee, Milwaukee, WI, (4) Medical College of Wisconsin, Milwaukee, WI, (5) Medical College of Wisconsin, Milwaukee, WI, (6) Medical College of Wisconsin, Milwaukee, WI, (7) Medical College of Wisconsin, Milwaukee, WI |
| TU-HI-SAN2-12 | Sub-Region Based Radiomics Analysis for Survival Prediction in Esophageal Tumors Treated by Radiotherapy P Yang1*, L Xu1 , Z Cao1 , Y Jiang1 , Y Xue1 , C Luo1 , S Wu2 ,Y Kuang3 , T Niu1 , (1) Zhejiang University, Hangzhou, Zhejiang, Peoples R China,(2) Hangzhou Cancer Hospital, Hangzhou, Zhejiang, Peoples R China,(3) University of Nevada, Las Vegas, Las Vegas, NV |
| TU-J345-GePD-F2-5 | Predictability of Radiation Pneumonitis of 4DCT Derived Ventilation Maps for Lung Cancer Patients T Lin*, S Kumar , J Liu, A Dayal , L Chen, R Price, C Ma , Fox Chase Cancer Center, Philadelphia, PA |
| TU-J345-GePD-F5-4 | Multi-Organ Segmentation Through Surrogate Labels and Classification of Intermediate Network Representations D Huff1*, A Weisman1 , T Bradshaw1 , R Jeraj1,2 , (1) University of Wisconsin-Madison, Madison, Wisconsin, (2) University of Ljubljana, Ljubljana, Slovenia |
| TU-J345-GePD-F5-5 | Self-Attention Based Deep Learning Probabilistic Parotid Gland Segmentation Quality Evaluation Using Dose Volume Histogram Analysis S Berry*, J Jiang , S Elguindi , M Hunt , J Deasy , H Veeraraghavan , Memorial Sloan Kettering Cancer Center, New York, NY |
| TU-J345-GePD-F6-1 | Correlation of Deformation Vector Field Error and Contour-Based Metrics in Unimodal Deformable Image Registration L Shi1*, S Barley2 , S Benedict3 , J Qiu1 , Y Rong3 , (1) Taishan Medical University, Taian, ,(2) Oncology Systems Limited (OSL), Shrewsbury, ,(3) UC Davis Cancer Center, Sacramento, CA |
| TU-J345-GePD-F6-6 | Esitmating Rigid Body Registration Ground Truth Using Combinatorial Affine Registration Optimization (CARO) T Guerrero , D Solis , A Yorke*, William Beaumont Hospital, Royal Oak, MI |
| TU-J345-GePD-F7-3 | A Controlled Study of Dose Accumulation in Intensity-Modulated Radiotherapy for Non-Small Cell Lung Cancer Based On Rigid Registration and Deformable Registration J Ren*, G Gong , Y Yin , Shandong Cancer Hospital Affiliated to Shandong University, Jinan, China; H Quan , School of Physics and Technology, Wuhan University, Wuhan, China |
| TU-J345-GePD-F9-1 | Bias in Dual-Energy CT Material Decomposition Caused by Photon Starvation X Jiang*, X Yang , D Hintenlang , R White, Dept of Radiology, Ohio State Univ, Columbus, OH |
| TU-J345-GePD-F9-2 | Characterizing the Impact of Beam Hardening Conditions On Iodine Maps and Virtual Non-Contrast Images On a Dual Energy CT Scanner C Olguin*, S Leon , I Barreto , University of Florida, Gainesville, FL |
| TU-J345-GePD-F9-3 | Improving Delineation Using Simultaneous Dual-Energy CT for Radiation Therapy Planning of Pancreatic Cancer G Noid*, D Schott , A Tai , D Prah , E Paulson , X Li , Medical College of Wisconsin, Milwaukee, WI |
| TU-J345-GePD-F9-4 | Longitudinal Variation and Correlation of Spectral CT Measurements Using An ACR CT Phantom X Duan*, Y Zhang , J Guild , J Anderson , UT Southwestern Medical Ctr at Dallas, Dallas, TX |
| TU-J345-GePD-F9-5 | Optimization of Calcium Inserts for Quality Assurance of Calcium Removal in Dual Energy Computed Tomography M Lawless1*, L Di Maso1 , J Huang1 , K Ruchala4 , J Miller1 , (1) University of Wisconsin-Madison, Madison, WI, (4) GAMMEX Inc., Madison, WI |
| TU-J345-GePD-F9-6 | Virtual Monochromatic Analysis in Spectral CT for Differentiation of Soft Tissues: Potentials and Challenges X Tang1*, W Long1 , H Xie1 , Y Ren2 , (1) Emory University School of Medicine, Atlanta, GA, (2) Sinovision Technologies, Beijing, |
| TU-L-225BCD-2 | A Dual-Reconstruction Method to Generate Motion Artifact-Free CBCT Images H Zhong*, X Li , Medical College of Wisconsin, Milwaukee, WI |
| TU-L-225BCD-3 | Convolutional Neural Network Method for Decomposition of Dual Energy CBCT Projections Into Basis Materials F Cassetta*, R Patel , M Haytmyradov , J Roeske , Loyola Univ Medical Center, Maywood, IL |
| TU-L-304-2 | Cone-Beam CT of Load-Bearing Surgical Hardware Using a Mechanical Model of Implant Deformation Q Cao*, S Liu , G Osgood , S Demehri , J Siewerdsen , J Stayman , W Zbijewski , Johns Hopkins University, Baltimore, MD |
| TU-L-304-3 | A Novel Contrast CT Based Quantitative Characterization of Surgical Resectability in Pancreatic Cancer Y Lao1*, J David2 , Z Fan2 , K Sheng1 , A Shiu3 , E Chang3 , R Tuli4 , W Yang3 , (1) UCLA School of Medicine, Los Angeles, CA, (2) Cedars Sinai Medical Center, Los Angeles, CA, (3) University of Southern California, Los Angeles, CA, (4) MSKCC,New York, NY |
| TU-L-304-6 | Understanding Reproducibility of Radiomic Features of Lung Nodules Under Heterogenous CT Acquisition and Reconstruction Conditions N Emaminejad*, M Wahi-Anwar , G Kim , M Brown , M McNitt-Gray , David Geffen School of Medicine at UCLA, Los Angeles, CA |
| TU-L-304-7 | Standardization in Quantitative Imaging: A Comparison of Radiomics Feature Values Obtained by Different Software Packages On a Set of Digital Reference Objects M McNitt-Gray1*, S Napel2 , J Kalpathy-Cramer3 , A Jaggi2 , D Cherezov4 , D Goldgof4 , H Yang5 , E Jones6 , M Muzi7 , N Emaminejad1 , M Wahi-Anwar1 , Y Balagurunathan8 , M Abdalah8 , B Zhao5 , L Hadjiiski9 , L Pierce7 , K Farahani10 , (1) David Geffen School of Medicine at UCLA, Los Angeles, CA, (2) Stanford Univ School of Medicine, Stanford, CA, (3) Massachusetts General Hospital, Boston, MA, (4) University of South Florida, Tampa, FL, (5) Columbia University, New York, NY, (6) UCSF, San Francisco, CA, (7) University of Washington, Seattle, WA (8) Moffitt Cancer Center, Tampa, FL, (9) University of Michigan, Ann Arbor, MI, (10) National Cancer Institute, Bethesda, MD |
| TU-L-304-8 | Prognosis Prediction with Homology-Based Radiomic Features Quantifying the Lung Tumor Malignancy in CT-Based Radiomics S Tanaka1*, N Kadoya1 , T Kajikawa1 , K Abe1, 2, S Dobashi3 , K Takeda3 , K Nakane4 , K Jingu1 , (1) Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan, (2) Department of Radiology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan, (3) Course of Radiological Technology, Health Sciences, Tohoku University Graduate School of Medicine, Sendai, Japan, (4) Department of Medicine, Osaka University Graduate School of Medicine, Osaka, Japan |
| WE-AB-221AB-1 | BEST IN PHYSICS (IMAGING): Designing Spatial-Spectral Filters for Spectral CT M Tivnan*, W Wang , S Tilley , J Stayman , Johns Hopkins University, Baltimore, MD |
| WE-AB-221AB-2 | Task-Based Spectral Optimization On Twin-Beam Dual-Energy CT: A Simulation Study L Ren*, S Tao , C McCollough , L Yu , Mayo Clinic, Rochester, MN |
| WE-AB-221AB-3 | Multi-Energy CT Using a Dual-Source Photon Counting Detector CT: Spectral and Dose Partition Optimization for Iodine Quantification S Tao*, L Ren , K Rajendran , C McCollough , S Leng , Mayo Clinic, Rochester, MN |
| WE-AB-221AB-4 | Assessing Lung Function Using Contrast Enhanced Dynamic 4D CT and Split Filter Dual Energy CT for Radiation Therapy Applications J Miller*, M Lawless , K Mittauer , A Wuschner , M Flakus , D Shanmuganayagam , J Meudt , J Huang , J Bayouth , University of Wisconsin, Madison, WI |
| WE-AB-221AB-6 | Noise Suppression in Image-Domain Multi-Material Decomposition for Dual-Energy CT Y Jiang*, Y Xue , P Yang , L Xu , C Luo , C Yang , T Niu , Zhejiang University, Hangzhou, Zhejiang, Peoples R China |
| WE-AB-221AB-7 | Noise Subtraction for Dual Energy CT Images Using A Deep Convolutional Neural Network A Missert*, L Yu , S Leng , C McCollough , Mayo Clinic, Rochester, MN |
| WE-AB-221AB-8 | Investigating the Use of Size Specific Calibrations to Perform Non Iodine Material Decomposition in Commercial Dual Energy CT Software J Miller*, L DiMaso , J Huang , M Lawless , Univ of Wisc Madison, Madison, WI |
| WE-AB-221AB-9 | Low Dose Ultra-High Resolution Sinus Imaging Using Photon-Counting Detector CT with Tin Filter K Rajendran*, W Zhou , S Tao , B Voss , M Bruesewitz , J Weaver , D DeLone , J Fletcher , C McCollough , S Leng , Mayo Clinic, Rochester, MN |
| WE-AB-221AB-10 | Coincidence Bins for Improving the Spectral Performance of Photon Counting Detectors S Hsieh1*, (1) Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California |
| WE-C1000-GePD-F2-3 | Development A Novel Convolutional Neural Network with Paced Transfer Learning for CT Based Liver Segmentation Z Zhang1*, X Pan2 , X Qi3 , (1) Xi'an University of Posts and Telecommunications, Xi'an,shaanxi, ,(2) Xi'an University of Posts and Telecommunications, Xi'an,shaanxi,(3) UCLA School of Medicine, Los Angeles, CA |
| WE-C1000-GePD-F2-4 | Hippocampal Segmentation From CT Scans with a Convolutional Nerual Network E Porter1*, P Fuentes2 , Z Siddiqui3 , A Thompson3 , T Guerrero3 , (1) Wayne State University, Detroit, MI, (2) Oakland University William Beaumont School of Medicine, Rochester, MI, (3) Beaumont Health, Royal Oak, MI |
| WE-C1000-GePD-F2-5 | Segmentation of Organs at Risk in Nasopharyngeal Cancer for Radiotherapy Using A Nested U-Net Architecture Fan SONG1,2*, Sihua WU1,3, Sijuan Huang1, Yunfei XIA1, Xin 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, 510060, China. (2) Guangdong University of Technology, Guangzhou, Guangdong, 511400, China. (3) Xinhua College of Sun Yat-sen University, Guangzhou, Guangdong, 510520,China. |
| WE-C1000-GePD-F5-2 | Comparison of Two CBCT Correction Methods for Daily Adaptive Therapy Dose Tracking D Pittock1*, N Lamba1 , S Ginsburg1 , I Dragojevic2 , A Kruzer1 , A Nelson1 , (1) MIM Software Inc., Cleveland, OH, (2) UC San Diego, Chula Vista, CA |
| WE-C1000-GePD-F6-2 | Deep Learning-Based Tomographic Image Reconstruction with Ultra-Sparse Projection Views L Shen1*, W Zhao2 , X Dai3 , L Xing4 , (1) Stanford University, Palo Alto, CA, (2) Stanford University, Palo Alto, CA, (3) Stanford University, Mountain View, CA, (4) Stanford University School of Medicine, Stanford, CA |
| WE-C1000-GePD-F9-4 | Investigation On KV Dependent SSDE Corrections for Low KV and Small Patient Scans: Phantom Based Evaluation Y Tian1 , X Cai1*, Y Yang1 , (1) Siemens Shanghai Medical Equipment Ltd., Shanghai |
| WE-C1000-GePD-F9-5 | Size-Specific Dose Estimates (SSDE) for Pelvic CT Image Acquisitions: TG204 Vs. TG220 and a New Density Scaling Method D Mihailidis1*, V Tsapaki2 , (1) University of Pennsylvania, Philadelphia, PA, (2) Konstantopoulio General Hospital, Anixi, Attiki, |
| WE-C1000-GePD-F9-6 | Variations of Size-Specific Dose Estimates (SSDE) Factors with Scan Mode A Abuhaimed1*, C Martin2 , (1) King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia,(2) University of Glasgow, Glasgow, UK |
| WE-C1030-GePD-F1-5 | Treatment Planning Strategies to Mitigate the Range and RBE Uncertainties in Proton Therapy for Targets in the Brain N Sahoo*, A Gautam , F Poenisch , T Williamson , X Zhang , Y Li , H Li , R Wu , M Gillin , D Grosshans , X Zhu , UT MD Anderson Cancer Center, Houston, TX |
| WE-C1030-GePD-F2-5 | Deep Learning for Automatic Real-Time Pulmonary Nodule Detection and Quantitative Analysis C Liu1*, S Hu2 , F Yin3 , (1) Duke Kunshan University, Suzhou, Jiangsu, (2) Duke Kunshan University, Suzhou, Jiangsu, (3) Duke University Medical Center, Durham, NC |
| WE-C1030-GePD-F5-1 | A Deep Learning Based Auto-Segmentation Method for Radiation Therapy of Head and Neck Cancer A Amjad1*, Z Chen2 , M Awan1 , M Shukla1 , C Yang2 , Q Zhou2 , X Li1 , (1) Medical College of Wisconsin, Milwaukee, WI, (2) Manteia Medical Technologies, Milwaukee, WI |
| WE-C1030-GePD-F5-2 | Automated Detection and Segmentation of Lung Tumors Using Deep Learning C Owens1,2*, D Rhee1,2 , D Fuentes3 , C Peterson2,4 , J Li5 , M Salehpour1 , L Court1,2,3 , J Yang1,2 , (1) Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, (2) The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX, (3) Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, (4) Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, (5) Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, TX |
| WE-C1030-GePD-F5-3 | Clinical Assessment of Deep Learning-Based Auto Segmentation On Nasopharyngeal Cancer J Wang*, S Sun , W Hu , Z Zhang Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China |
| WE-C1030-GePD-F5-5 | Utilizing the Clique Atrous Spatial Pyramid Pooling for Pancreas Segmentation M Yang1 , X Qi2 , S Tan1 (1) Huazhong University of Science and Technology, Wuhan, China,(2) UCLA School of Medicine, Los Angeles, CA |
| WE-C1030-GePD-F5-6 | How Many Sample Sizes Are Appropriate for Deep Learning Based Auto Segmentation for Head and Neck Cancer? F Yingtao , W Hu*, J Wang , S Chen , S Sun , Z Zhang , Fudan University Shanghai Cancer Center, Shanghai |
| WE-C1030-GePD-F6-3 | Generative Adversarial Network for Low Dose CT Denoising and Enhancement B Ye1 , X Qi2 , S Tan1*(1) Huazhong University of Science & Technology, Wuhan, China (2) UCLA School of Medicine, Los Angeles, CA |
| WE-C1030-GePD-F9-1 | Do Commercially Available In- Plane Bismuth Breast Shields Are Consistent with Patients Care? V Karami1 , M Albosof2 , M Najaran1 , M Gholami3 , H Khosravi4*, (1) Dezful University of Medical Sciences, Dezful,Iran (2) School of Technical and Engineering, Dezful Branch, Islamic Azad University, Dezful,Iran (3) Lorestan University of Medical Sciences, Khoram Abad,Iran (4) University of Mississippi Medical Center, Jackson, MS |
| WE-C1030-GePD-F9-2 | Skin Exposure Estimation From Annual Survey Data for Computed Tomography V Garcia*, W Wang , University of Oklahoma Health Science Center, Oklahoma City, OK |
| WE-C1030-GePD-F9-4 | Size-Specific CT Dose Modulation for Low-Contrast Detectability J James1*, V Rana2 , Y Liang3 (1) Indiana University, Imaging Sciences, Indianapolis, IN, (2) Houston Methodist Hospital, Houston, TX, (3) Indiana University Medical Center, Indianapolis, IN |
| WE-C1030-GePD-F9-6 | Ideal Broad-Beam Geometry/attenuation, Effective Energy, and Its Impact in CT Dosimetry N Ruiz Gonzalez*, G Clarke , UT Health Sciences Center, San Antonio, TX |
| WE-C930-GePD-F8-5 | Quantitative Analysis of Bony Anatomy Vs Soft Tissue Matching Using CBCT in Treatment of Pancreatic Cancer S Balyimez*, C Chen , E Parsai , University of Toledo Medical Center, Toledo, OH |
| WE-C930-GePD-F9-6 | Spectral Modulator With Flying Focal Spot: A New Concept of Full-Scale Multi-Energy Cone-Beam CT and Simultaneous Scatter Correction Hewei Gao*, Chengpeng Wu and Sen Wang, Tsinghua University, Beijing 100084, China |
| WE-D-TOUR-I-0 | Brain CT Perfusion K Little*, Ohio State University, Columbus, OH |
| WE-FG-304-6 | Quantification of Local Metabolic Tumor Volume Changes by Registering Blended 18F-FDG PET/CT Images for Prediction of Pathologic Tumor Response S Riyahi1*, W Choi2 , C Liu3 , S Nadeem1 , S Tan5 , H Zhong6 , W Chen7 , A Wu1 , J Mechalakos1 , J Deasy1 , W Lu1 , (1) Memorial Sloan Kettering Cancer Center, New York, NY, (2) University of Virginia, Charlottesville, VA, (3) National Taiwan University Hospital Yunlin Branch, Yunlin, (5) Huazhong University of Science & Technology, Wuhan, (6) Medical College of Wisconsin, Milwaukee, WI, (7) University of Maryland School of Medicine, Baltimore, MD |
| WE-FG-304-8 | Automated Registration-Based Longitudinal Lesion Matching On PET/CT V Santoro-Fernandes1*, D Huff1 , M Albertini2 , R Jeraj1,2,3 , (1) University of Wisconsin-Madison, Madison, WI, (2) University of Wisconsin Carbone Cancer Center, Madison, WI, (3) University of Ljubljana, Ljubljana, Slovenia |
| WE-FG-304-9 | Improve Deformable Imaging Registration Accuracy Using Pulmonary Vascular Extraction for Lung CT Images D Yang*, Y Fu , X Wu , H Li , Washington University School of Medicine, St. Louis, MO |
| WE-HI-SAN2-3 | Evaluation of a Pencil-Beam Scanning Proton Radiography System Using a Flat-Panel Imager J Harms1*, L Maloney2 , J Sohn1 , Y Lin1 , H Gao1 , A Erickson2 , T Liu1 , R Zhang1 , (1) Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322 (2) Nuclear and Radiological Engineering and Medical Physics Programs, George W. Woodruff Department of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332 |
| WE-HI-SAN2-7 | Stopping Power Map Estimation From Cone-Beam CT Using Deep Learning for CBCT-Guided Adaptive Radiation Therapy J Harms*, Y Lei , T Wang , B Ghavidel , W Stokes , T Liu , W Curran , J Zhou , M McDonald , X Yang , Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322 |
| WE-HI-SAN2-10 | Method for Fluence Field Optimization to Achieve Non-Convex Image Noise Prescriptions with Fluence-Modulated Proton CT J Dickmann*1, P Wesp1, S Rit2, M Pankuch3, R P Johnson4, V Bashkirov5, R W Schulte5, K Parodi1, G Dedes1, G Landry1,6, (1) Ludwig-Maximilians-Universitaet Muenchen, Munich, Germany, (2) Universite de Lyon, Lyon, France, (3) Northwestern Medicine Chicago Proton Center, Warrenville, IL, (4) U.C. Santa Cruz, Santa Cruz, CA, (5) Loma Linda University, Loma Linda, CA, (6) University Hospital, LMU Munich, Munich, Germany |
| WE-J-221CD-0 | Tailoring CT Protocol to Patient Age and Size with a Focus On Pediatric Patients Z Qi1*, F Ranallo2*, K Applegate3*, (1) Henry Ford Health System, Troy, MI, (2) University of Wisconsin, Madison, WI, (3) Kentucky Children's Hospital, Lexington, KY |
