LLM-driven Multimodal Target Volume Contouring in Radiation Oncology

arXiv:2311.01908v3 Announce Type: replace-cross
Abstract: Target volume contouring for radiation therapy is considered significantly more challenging than the normal organ segmentation tasks as it necessitates the utilization of both image and text-based clinical information. Inspired by the recent advancement of large language models (LLMs) that can facilitate the integration of the textural information and images, here we present a novel LLM-driven multimodal AI, namely LLMSeg, that utilizes the clinical text information and is applicable to the challenging task of target …

abstract advancement arxiv clinical contouring cs.cv eess.iv image information integration language language models large language large language models llm llms multimodal normal oncology segmentation tasks text therapy type