Autodelineation of Treatment Target Volume for Radiation Therapy Using Large Language Model-Aided Multimodal Learning

• Published in: International journal of radiation oncology, biology, physics Vol. 121; no. 1; p. 230
• Main Authors: Rajendran, Praveenbalaji, Chen, Yizheng, Qiu, Liang, Niedermayr, Thomas, Liu, Wu, Buyyounouski, Mark, Bagshaw, Hilary, Han, Bin, Yang, Yong, Kovalchuk, Nataliya, Gu, Xuejun, Hancock, Steven, Xing, Lei, Dai, Xianjin
• Format: Journal Article
• Language: English
• Published: United States 01.01.2025
• Subjects: Algorithms; Artificial Intelligence; Humans; Male; Oropharyngeal Neoplasms - radiotherapy; Prostatic Neoplasms - diagnostic imaging; Prostatic Neoplasms - radiotherapy; Radiotherapy Planning, Computer-Assisted - methods; Tumor Burden

Artificial intelligence-aided methods have made significant progress in the auto-delineation of normal tissues. However, these approaches struggle with the auto-contouring of radiation therapy target volume. Our goal was to model the delineation of target volume as a clinical decision-making problem...