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| 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-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 |
| PO-GePV-I-4 | Effect of the Oxygen Saturation On the Grayscale Value of Reconstructed Image Based On First-Order K-Space Modeling B Liu*, Z Xue , H Lin , J Xu , Z Wei , B Zhang , HFUT, Heifei, Anhui |
| 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-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-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-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-T-239 | Do We Still Need to Acquire a Treatment Planning CT? P Gates*, H Liu , T Hayes , N Koch , Q Shang , B Sintay , D Wiant , Cone Health, Greensboro, NC |
| 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-225BCD-2 | Evaluation of Tracking Accuracy Using Synthetic Color Fluoroscopic Images Based On the Deep Learning for Real-Time Tumor-Tracking Radiotherapy T Shiinoki*, Y Yuasa , K Fujimoto , Yamaguchi University, Ube |
| SU-F-303-4 | K-Nearest Neighbor Model-Based Approach for Classification of TI-RADS Class-4 Thyroid Nodules W Lu* , T Wang , W Lu , L Shi , K Hou , H Zhao , J Qiu , Taishan Medical University, Taian, Shandong |
| SU-F-SAN2-4 | Feasibility of CT-Only 3D Dose Prediction for VMAT Prostate Plans Using Deep Learning S Willems1*, W Crijns1 , E Sterpin1,2 , K Haustermans1 , F Maes1 , (1) KULeuven (2) UCLouvain |
| SU-I300-GePD-F8-1 | A Deep Learning Approach On Non Alcoholic Fatty Liver Disease Diagnosis Utilizing Ultrasound B-Mode Images and Liver Biopsy as Gold Standard I Gatos1 , S Tsantis1 , P Drazinos2 , P Zoumpoulis2 , I Theotokas2 , P Katsakiori1 , D Mihailidis3 , J Hazle4 , G C Kagadis1, 3*, (1) University of Patras, Rion, Greece, (2) Diagnostic Echotomography, Athens, Greece, (3) University of Pennsylvania, Philadelphia, PA, USA, (4) UT MD Anderson Cancer Center, Houston, TX, USA |
| SU-K-303-1 | Auto Segmentation of Organs at Risk in Thorax Computed Tomography Using Deep Convolutional Neural Networks M Haytmyradov1*, M Surucu1 , F Cassetta1 , J Roeske1 , (1) Loyola University Medical Center, Maywood, IL |
| TH-A-225BCD-2 | Improving Deformable Image Registration of 4DCTs Using a Generative Adversarial Deep Neural Network for Automated Lung Lobe Segmentation B Stiehl1*, M Lauria1 , I Barjaktarevic1 , P Lee1 , D Low1 , A Santhanam1 , (1) University of California, Los Angeles, Los Angeles, CA |
| TH-BC-225BCD-2 | Strategically Acquired Gradient Echo (STAGE) Imaging for MRI-Only Stereotactic Radiosurgery Planning E Florez*, E Haacke , C M. Howard , R Hamidi , A Fatemi , University of Mississippi Med. Center, Jackson, MS |
| TH-BC-303-5 | Extraction of Lung Tumor On KV Projection Images for Noninvasive Real Time Tumor Motion Tracking with the Transfer Learning Deep Segmentation Net Jury Committee Algorithm M Chao1*, J Wei2 , Y Lo1 , K Rosenzweig1 , (1) The Mount Sinai Medical Center, New York, NY, (2) City College of New York, New York, NY |
| 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-221AB-6 | Fluorescence Molecular Tomography/X-Ray Computed Tomography Dual-Modality Tumor Detection Using Active Targeting Nanoparticles and Effective Background Subtraction J Shi*, T Udayakumar , N Dogan , A Pollack , Y Yang , University of Miami Miller School of Medicine, Miami, FL |
| TU-AB-225BCD-3 | Dual Energy Bone Suppression Using Neural Networks M Haytmyradov1*, F Cassetta1, R Patel1, M Surucu1, H. Mostavafi2, J Roeske1, (1) Loyola University Medical Center, Maywood, IL, USA (2) Varian Medical Systems, Palo Alto, CA, USA |
| TU-AB-SAN2-10 | Robustness of Conditional Generative Adversarial Networks in Generating Head and Neck Synthetic CT Images for MR-Only Radiotherapy Treatment Planning P Klages*, I Benslimane , S Riyahi , J Jiang , M Hunt , J Deasy , H Veeraraghavan , N Tyagi , Memorial Sloan Kettering Cancer Center, New York, NY |
| 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-F9-5 | 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-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-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-F9-4 | 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-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-G-TOUR-I-0 | Brain CT Perfusion K Little*, Ohio State University, Columbus, OH |
| 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-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-F6-5 | Validation of Planning CT to CBCT Deformable Image Registration-Based Dose Calculation for Prostate Cancer Adaptive Radiotherapy X Zhang*, West China hospital of Sichuan university, Chengdu, Sichuan |
| WE-AB-225BCD-8 | Predicting Volumetric Expansion of Esophagus During Lung Radiotherapy C Wang*, S Riyahi , Y Hu , S Nadeem , N Tyagi , R Kuo, A Rimner , J Deasy , P Zhang , Memorial Sloan Kettering Cancer Center, New York, NY |
| 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-C930-GePD-F5-4 | Detecting Significant Nodal Volume Shrinkage During Treatment in Head-And-Neck Radiotherapy Using Image Saliency Y Hu*, C Polvorosa , C Tsai , S Fontenla, G Mageras , M Hunt , Memorial Sloan Kettering Cancer Center, New York, NY |
| WE-D-TOUR-I-0 | Brain CT Perfusion K Little*, Ohio State University, Columbus, OH |
| WE-J-303-5 | Analytical Grayscale Transformation for Gain-Setting Calibration in Quantitative Ultrasound Radiomics X He*, X Yang , J Wynne , D Yu , J Beitler , W Curran , T Liu , Emory University, Atlanta, GA |
