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Taxonomy: IM- CT: Machine learning, computer vision
| 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-303-7 | Order-Graph Regularized Sparse Dictionary Learning for Unsupervised Multi-Needle Detection in 3D Ultrasound Images Y Zhang , Y Lei , J Jeong , Z Tian , Y Liu , T Wang , T Liu , A Jani , W Curran , P Patel , X Yang*, Emory Univ, Atlanta, GA |
| 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-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-16 | Image Acquisition Technique for Nuclear Medicine Using Deep Profile Learning M Choi*, D Yoon , M Kim , T Suh , The Catholic University of Korea, College of MedicineSeoul |
| SU-E-225BCD-2 | A Benchmark for Breast Ultrasound Image Computer-Aided Diagnosis E Zhang1*, J Li2 , S Seiler3 , M Chen4 , W Lu5 , X Gu6 , (1) UT Southwestern Medical Center, Dallas, TX, (2) Guangdong General Hospital, Guangzhou, China, (3) UT Southwestern Medical Center, Dallas, TX, (4) UT Southwestern Medical Center, Dallas, TX, (5) UT Southwestern Medical Center, Dallas, TX, (6) UT Southwestern Medical Center, Dallas, TX |
| 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-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-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-G300-SPS-F4-4 | Comparison of Classifier Performance for Several Machine Learning Classification Tasks for Computer-Aided Diagnosis of Breast Cancer Using DCE-MRI M Vieceli1*, K Drukker2 , J Papaioannou2 , A Edwards2 , H Abe2 , M Giger2 , H Whitney1,2 , (1) Wheaton College, Wheaton, IL, (2) University of Chicago, Chicago, IL, |
| 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-I400-GePD-F8-3 | Image Synthesis in Multi-Contrast MRI with Deep Convolutional Generative Adversarial Networks D Kawahara1*, S Ozawa1 , A Saito1, K Miki1, Y Murakami1, T Kimura1, Y Nagata1, (1) Hiroshima University, Hiroshima |
| SU-I430-GePD-F9-4 | Quantitative Evaluation of Image Quality in Low Dose CT Images Obtained by Deep Learning D Lee*, H Kim , |
| SU-J400-CAMPUS-F1-2 | Combined Use of Gray Matter Volume and Quantitative Susceptibility Mapping to Predict Early Alzheimers Disease Using a Machine Learning-Based Optimized Combination-Feature Set HK Kim1 , HY Rhee2 , CW Ryu3 ,GH Jahng3*, (1) Radiology, Kyung Hee University Hospital, Seoul,Korea ,(2) Neurology, Kyung Hee University Hospital at Gangdong, Seoul,Korea ,(3) Radiology, Kyung Hee University Hospital at Gangdong, Seoul,Korea |
| 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-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 |
| TH-A-303-9 | MRI Radio Frequency Power Amplifier Linearization with Pre-Distortion Based On Artificial Neural Network W Lu*, W Lu , L Shi , K Hou , H Zhao , J Qiu , Department of Radiology, Taishan Medical University, Taian, Shandong |
| 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 |
| 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-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-F9-5 | 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-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-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-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-225BCD-4 | Convolutional Neural Network for Centroiding and Depth-Of-Interaction Localization in PET A LaBella*, W Zhao , AH Goldan , Stony Brook University, Stony Brook, NY |
| WE-AB-225BCD-5 | Harmonization of Radiomic Features of Breast Lesions Extracted From DCE-MRI Across Two Populations H Whitney1,2*, H Li1 , Y Ji1,3 , A Edwards1 , J Papaioannou1 , P Liu3 , M Giger1 , (1) University of Chicago, Chicago, IL, (2) Wheaton College, Wheaton, IL,(3) Tianjin Medical University Cancer Institute and Hospital, Tianjin, China |
| WE-AB-225BCD-12 | Musculoskeletal Tumor Classification On T2-Weighted MRI Using Probability Fusion Convolutional Neural Network and Support Vector Machine L Chen*, S Fisher , A Rodriguez , M Folkert , A Chhabra , S Jiang , J Wang , UT Southwestern Medical Center, Dallas, TX |
| 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-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-HI-303-5 | Support Vector Machine in the Differential Diagnosis of Benign and Malignant Thyroid Nodules T Wang*, L Shi , W Lu , J Qiu , W Lu , Taishan Medical University, Taian, Shandong |
| 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-J-303-3 | A Multi-Layer Perception Based Method for Thyroid Imaging Reporting and Data System Class-4 Thyroid Nodules Diagnosis T Wang*, W Lu , L Shi , J Qiu , K Hou , H Zhao , W Lu , Taishan Medical University, Taian, Shandong |
