We developed an algorithm to assess plan selection from a pre-existing plan library to unlock the full potential of plan-of-the-day (POTD) radiotherapy. The algorithm mimics nuanced human decision-making, automatically identifying the best plan (small- or med...
Author profile
Alex Dunlop, PhD
Joint Department of Physics, Institute of Cancer Research and The Royal Marsden NHS Foundation Trust
A Classification Model to Identify Target Selection Acceptability from a Library of Plans for Bladder Cancer Radiotherapy
Poster Program · Diagnostic and Interventional Radiology Physics
Automatic Classification of Pre-Existing Plan Acceptability As a Decision-Support Tool to Streamline Online Adaptive Radiotherapy
Online adaptive radiotherapy (oART) is time-consuming and resource-intensive. To alleviate this, we developed a tool combining autocontouring and image registration to classify pre-existing treatment plans (Planspre), defined as the offline reference plan or...
Proffered Program · Therapy Physics
BLUE RIBBON POSTER MULTI-DISCIPLINARY: Mspock: Multi Contrast Sparse-to-Precise Organs-at-Risk Contouring with Prior Knowledge for Pancreatic MR-Linac Radiotherapy
To develop an MR organs-at-risk (OAR) auto-contouring pipeline that is robust in severely limited-data settings across contrasts, specifically for MR-Linac pancreatic cancer treatments where full-volume manual contouring can take ~8h. We developed mSPOCK (mul...
Poster Program · Therapy Physics