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End-to-end breast cancer radiotherapy planning via LMMs with consistency embedding

Authors
 Kwanyoung Kim  ;  Yujin Oh  ;  Sangjoon Park  ;  Hwa Kyung Byun  ;  Joongyo Lee  ;  Jin Sung Kim  ;  Yong Bae Kim  ;  Jong Chul Ye 
Citation
 MEDICAL IMAGE ANALYSIS, Vol.105 : 103646, 2025-10 
Journal Title
MEDICAL IMAGE ANALYSIS
ISSN
 1361-8415 
Issue Date
2025-10
MeSH
1
Keywords
Algorithms ; Breast Neoplasms* / diagnostic imaging ; Breast Neoplasms* / radiotherapy ; Female ; Humans ; Radiotherapy Planning, Computer-Assisted* / methods
Abstract
Clinical report; Large multimodal model; Radiation oncology; Radiotherapy target volume; Segmentation
Article Number
 10.1016/j.media.2025.103646 
DOI
Recent advances in AI foundation models have significant potential for lightening the clinical workload by mimicking the comprehensive and multi-faceted approaches used by medical professionals. In the field of radiation oncology, the integration of multiple modalities holds great importance, so the opportunity of foundational model is abundant. Inspired by this, here we present RO-LMM, a multi-purpose, comprehensive large multimodal model (LMM) tailored for the field of radiation oncology. This model effectively manages a series of tasks within the clinical workflow, including clinical context summarization, radiotherapy strategy suggestion, and plan-guided target volume segmentation by leveraging the capabilities of LMM. In particular, to perform consecutive clinical tasks without error accumulation, we present a novel Consistency Embedding Fine-Tuning (CEFTune) technique, which boosts LMM's robustness to noisy inputs while preserving the consistency of handling clean inputs. We further extend this concept to LMM-driven segmentation framework, leading to a novel Consistency Embedding Segmentation (CESEG) techniques. Experimental results including multi-center validation confirm that our RO-LMM with CEFTune and CESEG results in promising performance for multiple clinical tasks with generalization capabilities.
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiation Oncology (방사선종양학교실) > 1. Journal Papers
Yonsei Authors
Kim, Yong Bae(김용배) ORCID logo https://orcid.org/0000-0001-7573-6862
Kim, Jinsung(김진성) ORCID logo https://orcid.org/0000-0003-1415-6471
Park, Sang Joon(박상준)
Byun, Hwa Kyung(변화경) ORCID logo https://orcid.org/0000-0002-8964-6275
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/207411
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