Non‐convex IMRT treatment planning using deep inverse optimization

Background Intensity‐modulated radiation therapy (IMRT) utilizes inverse optimization to calculate beamlet intensities, achieving clinical dose objectives for tumors while minimizing dose to organs‐at‐risk (OARs). However, incorporating non‐convex dose‐volume constraints into IMRT planning is challe...

Full description

Bibliographic Details

Published in:	Medical physics (Lancaster) Vol. 52; no. 11; pp. e70141 - n/a
Main Authors:	Lei, Yang, Zhang, Jiahan, Liu, Tian
Format:	Journal Article
Language:	English
Published:	United States 01.11.2025
Subjects:	Carcinoma, Non-Small-Cell Lung - radiotherapy deep inverse optimization Deep Learning Humans IMRT auto‐planning Lung Neoplasms - radiotherapy non‐convex programming Organs at Risk - radiation effects Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted - methods Radiotherapy, Intensity-Modulated - methods IMRT auto‐planning non‐convex programming deep inverse optimization
ISSN:	0094-2405, 2473-4209, 2473-4209
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!