An end-to-end multifunctional AI platform for intraoperative diagnosis.

ABSTRACT: Intraoperative frozen section diagnosis provides essential, real-time histological insights to guide surgical decisions. However, the quality of these time-sensitive sections is often suboptimal, posing significant diagnostic challenges for pathologists. To address these limitations, we utilized over 6700 whole slide images to develop GAS, a comprehensive platform comprising three modules: Generation, Assessment, and Support modules. The Generation module, based on a GAN-driven multimodal network guided by FFPE-style text descriptions, demonstrated effective enhancement of frozen section quality across various organs. The Assessment module, which fine-tuned quality control models using pathological foundation models, showed substantial improvements in microstructural quality for the genera

SUBMITTER: Zheng X 

PROVIDER: S-EPMC12277390 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature