Pediatric craniospinal irradiation (CSI) autosegmentation is challenging due to small, age-variable anatomy. Performance of a pediatric-trained in-house pipeline was compared with atlas-based and commercial AI methods for pediatric CSI organs at risk (OARs) u...
Author profile
Ozgur Ates, PhD
St. Jude Children's Research Hospital
Built for Children: A Pediatric-Trained Hybrid Autosegmentation Pipeline for Craniospinal Irradiation
Poster Program · Therapy Physics
Complete Optimization of 4π Monte Carlo-Based Proton Arc Technique (COMPACT): A Proof-of-Concept
Current proton beam-angle optimization methods are constrained by limited angular candidate sets and the high computational cost of Monte Carlo (MC)-based dose evaluation, hindering practical implementation of full-sphere (4π) optimization. We propose a 4π be...
Proffered Program · Therapy Physics
LET/Rbe Optimization and Evaluation In Proton Therapy Treatment Planning
Therapy Physics
Invited Program · Therapy Physics
BLUE RIBBON POSTER MULTI-DISCIPLINARY: Clinical Implementation of a Knowledge-Based Quality Assurance Tool Using CT and Shape Radiomics for Autosegmentation In Pediatric Craniospinal Irradiation
Automated segmentation is increasingly integrated into radiotherapy planning workflows; however, ensuring reliable quality assurance (QA) remains challenging, particularly in pediatric patients due to substantial anatomical variability. In this study, we leve...
Poster Program · Therapy Physics