This work presents a public project on the Cancer Genomics Cloud (CGC) platform for reproducible, out-of-the-box application of analysis workflows for pre-trained radiological and radiotherapy AI models; the first and only such project supporting analysis of...
Author profile
Jue Jiang, PhD
Memorial Sloan Kettering Cancer Center
A Cancer Genomics Cloud Project for Radiological and Radiotherapy Image Analyses
Poster Program · Therapy Physics
AI Deformable Dose Accumulation and Patient-Specific Uncertainty for MR-Guided Radiotherapy of Locally Advanced Pancreatic Cancer
Dose accumulation using deformable image registration (DIR) enables a more accurate evaluation of delivered dose in adaptive radiotherapy, allowing evaluation of discrepancies between planned and delivered treatments. However, different DIR algorithms produce...
Poster Program · Therapy Physics
Quantifying Primary and Lymph Node Tumor Volume Reduction and Mass Loss during Radiotherapy
Early assessment of radiotherapy response is essential for adaptive treatment planning and digital-twin development. Longitudinal quantification of tumor volume and mass changes depends on reliable deformable image registration (DIR), which remains challengin...
Poster Program · Therapy Physics