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Taxonomy: TH- Brachytherapy: Treatment planning using machine learning/automation
| BReP-SNAP-M-23 | Automatic Location and Size Selection of Round Applicators for AccuBoost Treatments F West1,2*, S Roles1,2, J Patrick2,3, R Munbodh2,3, M Rivard2,3, J Hepel2,3, K Leonard2,3, D Wazer2,3, Z Saleh2,3, (1) University of Rhode Island, Kingston, RI, (2) Rhode Island Hospital, Providence, RI, (3) Warren Alpert Medical School of Brown University, Providence |
| BReP-SNAP-T-141 | What Knowledge-Based Dose Prediction Models Tell Us About Ovoid Vs. Ring Based Brachytherapy Applicators K Kallis*, B Covele, A Simon, D Brown, D Scanderbeg, K Kisling, C Yashar, J Einck, L Mell, J Mayadev, K Moore, S Meyers, UC San Diego, La Jolla, CA |
| PO-GeP-T-144 | Automation of Eyeplaque Procedures for Greater Integration and Safety Q Diot*, D Westerly, M Miften, University of Colorado School of Medicine, Aurora, CO |
| PO-GeP-T-164 | Can Knowledge-Based Dose Prediction Models Inform Brachytherapy Needle Decision-Making for Cervical Cancer? K Kallis*, D Brown, D Scanderbeg, K Kisling, B Covele, A Simon, C Yashar, J Einck, L Mell, J Mayadev, K Moore, S Meyers, UC San Diego, La Jolla, CA |
| PO-GeP-T-183 | CivaSheet Commissioning and Workflow Planning S Morelli1*, J Woollard1, A Ayan1, N Gupta1, (1) The Ohio State University, Columbus, OH |
| TH-A-TRACK 3-2 | Accurate Post-Implantation Dose Reconstruction of CivaSheet, Aided by Machine Learning Techniques I Veltchev*, R Price, X Chen, K Howell, J Meyer, C Ma, Fox Chase Cancer Center, Philadelphia, PA |
| TU-EF-TRACK 3-9 | Knowledge-Based Three-Dimensional Dose Prediction for Tandem-And-Ovoid Brachytherapy K Cortes*, A Simon, K Kallis, J Mayadev, S Meyers, K Moore, University of California San Diego, La Jolla, CA |