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Keywords: reconstruction
| MO-IePD-TRACK 3-4 | High-Quality CBCT Reconstruction From Sparse and Limited-Size Projections Using a Joint Deformable Registration and Reconstruction Network (Reg-ReconNet) Y Zhang*, UT Southwestern Medical Ctr at Dallas, Dallas, TX |
| MO-IePD-TRACK 6-5 | Geometry Optimization and Optical Sectioning for In-Water Cherenkov Dosimetry of Large and Small Photon Beams Y Zlateva1*, B Muir2, I El Naqa3, J Seuntjens4, (1) Duke University, Durham, NC, (2) National Research Council, Ottawa, ON, (3) Moffitt Cancer Center, Tampa, FL, (4) McGill University, Montreal, QC |
| PO-GePV-I-21 | Sparse-View CT Reconstruction Via Generative Adversarial Network (GAN) Using Fully Convolutional DenseNet (FC-DenseNet) I Park*, J Chun, B Choi, S Yoo, J Kim, H Kim / Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea |
| PO-GePV-T-30 | Investigation of Impact of Systematic Errors in Applicator Reconstruction On Doses of Organs at Risk and Target Volumes in Intracavitary Brachytherapy G Singh1*, A Mourya2, B SINGH3, D Thaper4, R Kamal4, A Oinam1, V Kumar3, B Rai1, (1) Post Graduate Institute of Medical Education and Research, ,Chandigarh, IN, (2) Banaras Hindu university, Varanasi, UP, IN, (3) Centre for Medical Physics, Punjab University, Chandigarh, IN, (4) ILBS, Delhi, IN |
| SU-AB-TRACK 3-0 | SIIM-AAPM Joint Symposium On Machine Intelligence in Medical Imaging B Landman1*, K Brock2*, J Fessler3*, K Andriole4*, (1) Vanderbilt University Medical Center, Nashville, TN, (2) UT MD Anderson Cancer Center, Houston, TX, (3) University of Michigan, Ann Arbor, MI, (4) Brigham & Women's Hospital, Harvard Medical School, Branford, CT |
| SU-AB-TRACK 3-1 | Introduction B Landman1*, K Brock2*, J Fessler3*, K Andriole4*, (1) Vanderbilt University Medical Center, Nashville, TN, (2) UT MD Anderson Cancer Center, Houston, TX, (3) University of Michigan, Ann Arbor, MI, (4) Brigham & Women's Hospital, Harvard Medical School, Branford, CT |
| SU-AB-TRACK 3-2 | Challenges and Opportunities in Validation of AI for Medical Imaging B Landman1*, K Brock2*, J Fessler3*, K Andriole4*, (1) Vanderbilt University Medical Center, Nashville, TN, (2) UT MD Anderson Cancer Center, Houston, TX, (3) University of Michigan, Ann Arbor, MI, (4) Brigham & Women's Hospital, Harvard Medical School, Branford, CT |
| SU-AB-TRACK 3-3 | Harnessing AI to Enable Advanced Image-Guidance in Interventional Procedures B Landman1*, K Brock2*, J Fessler3*, K Andriole4*, (1) Vanderbilt University Medical Center, Nashville, TN, (2) UT MD Anderson Cancer Center, Houston, TX, (3) University of Michigan, Ann Arbor, MI, (4) Brigham & Women's Hospital, Harvard Medical School, Branford, CT |
| SU-AB-TRACK 3-4 | Joint Optimization of Learning-Based Image Reconstruction and K-Space Trajectories for MRI B Landman1*, K Brock2*, J Fessler3*, K Andriole4*, (1) Vanderbilt University Medical Center, Nashville, TN, (2) UT MD Anderson Cancer Center, Houston, TX, (3) University of Michigan, Ann Arbor, MI, (4) Brigham & Women's Hospital, Harvard Medical School, Branford, CT |
| SU-AB-TRACK 3-5 | Standards-Based Integration of AI Tools into Clinical Practice B Landman1*, K Brock2*, J Fessler3*, K Andriole4*, (1) Vanderbilt University Medical Center, Nashville, TN, (2) UT MD Anderson Cancer Center, Houston, TX, (3) University of Michigan, Ann Arbor, MI, (4) Brigham & Women's Hospital, Harvard Medical School, Branford, CT |
| SU-AB-TRACK 3-6 | Q&A B Landman1*, K Brock2*, J Fessler3*, K Andriole4*, (1) Vanderbilt University Medical Center, Nashville, TN, (2) UT MD Anderson Cancer Center, Houston, TX, (3) University of Michigan, Ann Arbor, MI, (4) Brigham & Women's Hospital, Harvard Medical School, Branford, CT |
| SU-F-TRACK 3-4 | Image Quality Evaluation of a Compressed-Sensing Algorithm for Image Reconstruction in Dedicated Cone-Beam Breast CT Using Offset-Detector S Vedantham*, H Tseng, A Karellas, University of Arizona, Tucson, AZ |
| SU-IePD-TRACK 1-1 | Electroacoustic Tomography for Monitoring Electroporation in Real Time S Wang1*, A Zarafshani2, L Xiang1, (1) University of California, Irvine, Irvine, CA, (2) Eastern Washington University, Spokane, WA |
| SU-IePD-TRACK 3-3 | Intelligent CT Reconstruction with Simultaneous Learning of Reconstruction Policy and Image Quality Assessment Using Quality-Guided Deep Reinforcement Learning Y Gao*, C Shen, M Tsai, Y Gonzalez, L Chen, X Jia, The University of Texas Southwestern Medical Center, Dallas, TX |
| TH-C-TRACK 3-1 | BEST IN PHYSICS (IMAGING): Parallel Imaging Stream for Multi-Purpose Real-Time Adaptive MRI-Guided Prostate Radiotherapy T Bruijnen1,2*, P Borman1, T Schakel1, B Raaymakers1, (1) Department of Radiotherapy, University Medical Center Utrecht, Utrecht, UT, NL, (2) Computational Imaging Group for MRI diagnostics and therapy, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, UT, NL |
| TH-IePD-TRACK 2-3 | Leveraging Prior Knowledge to Reconstruct Quantitative MR Relaxation Maps to Investigate Glioma Tumor Heterogeneity X Zhao1*, D Parsons2, Z Iqbal1, (1) University of Alabama - Birmingham, Birmingham, AL, (2) UT Southwestern Medical Center, Dallas, TX |
| TU-C-TRACK 3-1 | A Deep Learning Technique for Projection Interpolation in CBCT Reconstruction K Lu1*, Z Zhang1, L Ren2, F Yin2, (1) Duke University, Durham, NC, (2) Duke University Medical Center, Durham, NC |
| TU-C-TRACK 3-3 | A Method for 4D Cone-Beam CT in Under 20 Seconds with New Generation Linacs S Blake*, O Dillon, R O'Brien, ACRF Image-X Institute, University of Sydney, Sydney, NSW, AU |
| TU-C-TRACK 3-5 | Faster Safer Clearer 4DCBCT: Results of the ADAPT Clinical Trial O Dillon1*, B Lau1, T Reynolds1, P Keall1, S Vinod2, A Wallis3, S Smith4, J Sonke5, R O'Brien1, (1) University of Sydney, Sydney, NSW, AU, (2) University Of New South Wales, Sydney, NSW, AU,(3) Liverpool Hospital Sydney, Sydney, NSW, AU, (4) South Western Sydney Lhd, Sydney, NSW, AU, (5) Netherlands Cancer Institute, Amsterdam, NH, NL |
| TU-C-TRACK 3-6 | Rapid Low Dose 4DCBCT B Lau1*, O Dillon1, T Reynolds1, P Keall1, J Sonke2, S Vinod3,4, R O'Brien1, (1) ACRF Image X Institute, University of Sydney, Sydney, NSW, AU, (2) Netherlands Cancer Institute, Amsterdam, (3) University Of New South Wales, Sydney, NSW, AU, (4) Liverpool Hospital Sydney, Sydney, NSW, AU |
| TU-C-TRACK 3-7 | Reference-Free, Learning-Based Rigid Motion Compensation in Cone-Beam CT for Interventional Neuroradiology H Huang1*, J Siewerdsen1,2, W Zbijewski1, C Weiss2, T Ehtiati3, A Sisniega1, (1) The Johns Hopkins University, Baltimore, MD (2) Russell H. Morgan Department of Radiology, Johns Hopkins University, Baltimore, MD (3) Siemens Healthineers, Forchheim, Germany |
| TU-F-TRACK 3-4 | Ordered Subsets PWLS Reconstruction of Multi-Layer Detector MV-CBCT Data Using TIGRE M Jacobson1*, M Lehmann2, P Huber2, M Myronakis1, T Harris1, I Valencia Lozano1, 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 |
| TU-F-TRACK 3-5 | Reconstructing Dual KV Data Using the COSSCIR “One-Step” Direct Inversion Algorithm B Rizzo1*, E Sidky2, T Schmidt1, (1) Marquette University, Milwaukee, WI, (2) University of Chicago, Chicago, IL |
| WE-F-TRACK 3-3 | A Novel End-To-End Deep Learning Based Beamformer for Flexible Array Ultrasound Transducer X Huang*, M Lediju Bell, K Ding, Johns Hopkins University, Baltimore, MD |
| WE-IePD-TRACK 1-4 | Dictionary-Learning Iterative Reconstruction for Sparse Data, Slot-Scanning, Breast CT C Zhao1*, W Wang1, A Leong1, S Bambot2, J W Stayman1, (1) Johns Hopkins University, Baltimore, MD, (2) Fischer Imaging, West Hills, CA |
| WE-IePD-TRACK 1-6 | Reducing Scan Time and Dose: Motion Compensated Reconstruction for Adaptive 4DCBCT B Lau1*, O Dillon1, T Reynolds1, P Keall1, J Sonke2, S Vinod3,4, R O'Brien1, (1) ACRF Image X Institute, University of Sydney, Sydney, NSW, AU, (2) Netherlands Cancer Institute, Amsterdam, (3) University Of New South Wales, Sydney, NSW, AU, (4) Liverpool Hospital Sydney, Sydney, NSW, AU |
| WE-IePD-TRACK 1-7 | A Geometry-Guided Deep Learning Technique for CBCT Reconstruction K Lu1*, L Ren2, F Yin2, (1) Duke University, Durham, NC, (2) Duke University Medical Center, Durham, NC |