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Taxonomy: IM- MRI : Image Reconstruction
| 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-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-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-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-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 |
| PO-GePV-I-20 | Deep Learning for High Spatial Resolution X-Ray Luminescence Computed Tomography X Dai , K Cheng*, W Zhao , L Xing , Stanford University School of Medicine, Stanford, CA |
| 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 |
| 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-G300-SPS-F4-2 | Effects of Acoustic Heterogeneity in X-Ray-Induced Acoustic Computed Tomography C Cochran1*, P Samant2 , L Xiang3 , (1) University of Oklahoma, Norman, OK, (2) University of Oklahoma, Norman, OK, (3) University of Oklahoma, Norman, OK |
| 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-303-3 | Accelerating MR Image Acquisition with Sparse Sampling And Integration of Self-Attention Into a Deep Convolutional Neural Network Y Wu1*, Y Ma2 , J Du2 , J Liu3, D Capaldi1 , L Xing1 , (1) Stanford Univ School of Medicine, Stanford, CA, (2) University of California San Diego, San Diego, CA, (3) University of California San Francisco, San Francisco, CA |
| TH-A-303-4 | Comparison Between Deep Learning and Total Generalized Variation Methods for Fast MRI Z Jiang*, F Yin, Z Chang , Duke University Medical Center, Durham, NC |
| 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-L-225BCD-1 | A Cascade Deep Network to Improve Parallel MRI Reconstruction T Chao1*, T Lin2 , M Wu2 , (1) Department of Radiology, Mayo Clinic, Rochester, MN, U.S.A. (2) Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan |
| 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-F8-5 | Parameter Characterization in a GRAPPA Reconstruction Algorithm for Spectroscopic Imaging J Weygand*, M Ladd , P Bachert , A Korzowski , German Cancer Research Center, Heidelberg, Germany |
