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Taxonomy: IM/TH- Image Analysis (Single Modality or Multi-Modality): Computer-aided decision support systems (detection, diagnosis, risk prediction, staging, treatment response assessment/monitoring, prognosis prediction)
| MO-G-202-6 | In Vivo Cherenkov Imaging Analysis Can Detect Inter- and Intra-Fractional Radiotherapy Treatment Anomalies S Decker1*, D Alexander1, P Bruza1, 2, R Zhang1,3,4, E Chen5, L Jarvis3,4, D Gladstone1, B Pogue1,2,6, (1) Thayer School of Engineering, Dartmouth College, Hanover, NH, (2) DoseOptics, LLC, Lebanon, NH, (3) Norris Cotton Cancer Center, Dartmouth-Hitchcock, Lebanon, NH, (4) Geisel School of Medicine, Dartmouth College, Hanover, NH, (5) Cheshire Medical Center, Keene, NH, (6) Department of Medical Physics, University of Wisconsin-Madison, Madison, WI |
| PO-GePV-M-59 | Brain Metastasis Stereotactic Radiosurgery Radiomics-Based Outcome Prediction Accuracy Is Dependent On Metastasis Volume and MRI Scanner D DeVries1,2*, F Lagerwaard3, J Zindler4,5, T Yeung6, G Rodrigues1,2, G Hajdok1,7, A Ward1,2, (1) Western University, London, ON, CA, (2) London Regional Cancer Program, London, ON, CA, (3) Amsterdam UMC, Amsterdam, NL, (4) Haaglanden Medical Centre, Den Haag, NL, (5) Holland Proton Therapy Centre, Delft, NL, (6) Reflexion Medical Inc, (7) Niagara Health, ON, CA |
| PO-GePV-M-167 | Feasibility Study of Quantifying the Dosimetric Discrepancies of Planned Dose in Comparison to Delivered Dose Utilizing Daily Cone-Beam Computed Tomography (CBCT) T Cuthbert1*, S Stathakis2, P Mavroidis3, N Papanikolaou4, W Jones5, (1) UT Health Sciences Center, San Antonio, TX, (2) Mays Cancer Center - MD Anderson Cancer Center, San Antonio, TX, (3) University of North Carolina, Chapel Hill, NC, (4) University of Texas HSC SA, San Antonio, TX, (5) University of Texas HSC San Antonio, San Antonio, TX |
| PO-GePV-M-301 | Predicting Radiotherapy Induced Anatomic Change for Head Neck Cancer Patients Using Vision Transformer K Wang*, A Andrade, M Dohopolski, J Wang, UT Southwestern Medical Center, Dallas, TX |
| PO-GePV-M-337 | A 2D/3D Integrated Network for Breast Tumor Classification X Chen1, X Wang1*, J Lv1, Z Zhou2, (1) Xi'an Jiaotong University, Xi'an, 61, CN, (2)University Of Kansas Medical Center,Kansas City, KS. |
| PO-GePV-M-338 | Establishing Reliable Medical Prediction Model Based On Uncertainty Estimation D Feng1, X Chen1, X Wang1*, Z Zhou2, (1) Xi'an Jiaotong University, Xi'an, 61, CN, (2) University Of Kansas Medical Center,Kansas City, KS. |
| PO-GePV-M-356 | A Practical Approach for Improving Quantitative Assessment of Native Renal Recovery Using Multi-View Tc-99m DTPA Renal Scintigraphy for SLK Patients with 3+ Kidneys J Zhang1*, (1) Radiology, The Ohio State University, Columbus, OH |
| SU-H400-IePD-F5-1 | A Graph Attention Network Combining Both Radiomics and Clinical Data for Improved and Interpretable Prediction of Lymph Node Invasion in High-Grade Prostate Cancers M Larose*1, 2, 3, N Touma3, N Raymond4, D Leblanc1, 2, 3, F Rasekh3, B Neveu3, H Hovington3, M Vallières4, F Pouliot3, L Archambault1, 2, 3, (1) Department of physics, Université Laval, Qc, Canada (2) Centre de recherche sur le cancer, Qc, Canada (3) CHU de Québec, QC, Canada (4) Department of computer science, Université de Sherbrooke, QC, Canada |
| TH-C-202-3 | Delta Radiomic Features Predict Failure and Survival Outcomes for Surgically Resected Pancreatic Cancer Patients Treated with Neoadjuvant Therapy K Wang*, A Elamir, J Karalis, S Enrico, P Polanco, T Aguilera, M Ligorio, J Wang, UT Southwestern Medical Center, Dallas, TX |
| TU-D930-IePD-F2-4 | A Deep Learning Model with Radiomics Analysis Integration for Glioblastoma Post-Resection Survival Prediction Z Hu1*, Z Yang2, J Zhao1, H Zhang1, E Vaios2, K Lafata2, F Yin2, C Wang2, (1) Duke Kunshan University, Kunshan, Jiangsu, China (2) Duke University, Durham, NC |
| TU-D930-IePD-F8-4 | Extraction of Osteosclerotic Regions Using Diffusion Equation K Doi1*, Y Anetai2, H Takegawa2, Y Koike2, S Nakamura2, T Nishio1, (1) Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Suita city, Osaka, JP, (2) Department of Radiation Oncology, Kansai Medical University Hospital, Hirakata city, Osaka, Japan |
| TU-GH-BRB-1 | Opportunistic CT AI Screening for Low Bone Mineral Density S Fahrenholtz*, I Banerjee, A Tariq, B Patel, W Sensakovic, Mayo Clinic Arizona, Phoenix, AZ |
| TU-GH-BRB-3 | Augmented Colorectal Cancer Detection Using Self-Attention-Incorporated Deep Learning X Jia1, S Sang1, Y Zhou2, H Ren1, M Laurie1, M Islam1, O Eminaga1, J Liao1, L Xing1*, (1) Stanford University School of Medicine, Stanford, CA, (2) University of California Santa Cruz, Santa Cruz, CA |