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Taxonomy: IM/TH- Image Analysis (Single Modality or Multi-Modality): Machine learning
| MO-FG-BRB-2 | A Neural Ordinary Differential Equation Model for Visualizing Deep Neural Network Behaviors in Multi-Parametric MRI Based Glioma Segmentation Z Yang1*, Z Hu2, H Ji3, K Lafata1, S Floyd1, F Yin1, C Wang1, (1) Duke University, Durham, NC, (2) Duke Kunshan university, Kunshan, Jingsu, China, (3) North Carolina State University, Raleigh, NC |
| PO-GePV-I-70 | Bridging the Gap Between Machine Learning and Clinicians Through Interpretable AI in Head and Neck Cancer Assessment Y Wang1, W Duggar2*, T Thomas2, P Roberts2, R Gatewood2, S Vijayakumar2, L Bian1, H Wang1, (1) Mississippi State University, ,,(2) University of Mississippi Med. Center, Jackson, MS, |
| PO-GePV-M-157 | Unsupervised CBCT-CT Synthesis for Prostate Radiotherapy Treatment with Contrastive Learning Y Pang*, X Chen, T Royce, A Wang, G Szalkowski, S To, P Yap, J Lian, University of North Carolina, Chapel Hill, NC |
| PO-GePV-M-180 | Multimodality Image Registration and Fusion Using Deep Learning for Radiotherapy Planning A Ratke*1, E Darsht1, C Baeumer2, B Spaan1, K Kroeninger1, (1) TU Dortmund University, Dortmund, DE, (2) West German Proton Therapy Centre Essen, Essen, DE |
| PO-GePV-M-345 | Automatic Segmentation Algorithms Improve the Efficiency and Inter-Observer Agreement of Gross Target Volumes Contours E Czeizler1, J Pajula2, H Polonen3, K Antila4, K Lehtio5, J Lehto6, A Tiulpin7, A Maslowski8, M Hakala9, E Kuusela10, K Bush11*, (1) Varian Medical Systems Finland, Helsinki, FI, (2) VTT Technical Research Center of Finland, Tampere, ,FI, (3) VTT Technical Research Center of Finland, Tampere, FI, (4) VTT Technical Research Center of Finland, Tampere, FI, (5) Oulu University Hospital, Department of Oncology and Radiotherapy, Oulu, FI, (6) Oulu University Hospital, Department of Oncology and Radiotherapy, Oulu, ,FI, (7) Ailean Technologies Oy, FI, (8) Varian Medical Systems, Palo Alto, CA, (9) Varian Medical Systems Finland, Helsinki, FI, (10) Varian Medical Systems Finland, Helsinki, FI, (11) Stanford University, Stanford, CA |
| SU-E-BRB-5 | Comparing Transfer Learning, Data Augmentation, and Data Expansion in the Improvement of Medical Image Generation M Woodland1,2*, J Wood1, B Anderson4, S Kundu1, E Lin1, E Koay1, B Odisio1, C Chung1, H Kang1, A Venkatesan1, S Yedururi1, B De1, Y Lin1, A Patel2,3, K Brock1, (1) The University of Texas M.D. Anderson Cancer Center, Houston, TX, (2) Rice University, Houston, TX, (3) Baylor College of Medicine, Houston, TX, (4) University of California San Diego, San Diego, CA |
| TH-E-BRC-1 | A Systematic Comparison of DNN-Based Lung CT Elastography Using Auto-Encoder, U-Net, Conditional and Cycle Generative Adversarial Network Techniques B Stiehl*, M Lauria, L Naumann, D O'Connell, P Boyle, I Barjaktarevic, D Low, A Santhanam, UCLA, Los Angeles, CA |
| TU-I345-IePD-F5-2 | A Radiomics-Integrated Deep-Learning Model for Identifying Radionecrosis Following Brain Metastasis Stereotactic Radiosurgery J Zhao1*, Z Yang1, Z Hu2, E Vaios1, D Carpenter1, S Floyd1, K Lafata1, F Yin1, C Wang1, (1) Duke University, Durham, NC, (2) Duke Kunshan University, Kunshan, Jiangsu, China |
| WE-C1030-IePD-F2-3 | Realistic Respiratory Motion Simulation Using Deep Learning D Lee*, S Nadeem, Y Hu, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY |