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使用共聚焦激光内镜的基于人工智能的胃癌实时组织病理学

Artificial intelligence-based real-time histopathology of gastric cancer using confocal laser endomicroscopy.

作者信息

Cho Haeyon, Moon Damin, Heo So Mi, Chu Jinah, Bae Hyunsik, Choi Sangjoon, Lee Yubin, Kim Dongmin, Jo Yeonju, Kim Kyuyoung, Hwang Kyungmin, Lee Dakeun, Choi Heung-Kook, Kim Seokhwi

机构信息

Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.

Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea.

出版信息

NPJ Precis Oncol. 2024 Jun 14;8(1):131. doi: 10.1038/s41698-024-00621-x.

DOI:10.1038/s41698-024-00621-x
PMID:38877301
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11178780/
Abstract

There has been a persistent demand for an innovative modality in real-time histologic imaging, distinct from the conventional frozen section technique. We developed an artificial intelligence-driven real-time evaluation model for gastric cancer tissue using confocal laser endomicroscopic system. The remarkable performance of the model suggests its potential utilization as a standalone modality for instantaneous histologic assessment and as a complementary tool for pathologists' interpretation.

摘要

对于一种不同于传统冷冻切片技术的实时组织学成像创新模式一直存在持续需求。我们使用共聚焦激光内镜系统开发了一种用于胃癌组织的人工智能驱动的实时评估模型。该模型的卓越性能表明其有潜力作为一种独立的即时组织学评估模式以及作为病理学家解读的辅助工具加以利用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cacb/11178780/bfd2ea1a5278/41698_2024_621_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cacb/11178780/fe74021ed617/41698_2024_621_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cacb/11178780/bfd2ea1a5278/41698_2024_621_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cacb/11178780/fe74021ed617/41698_2024_621_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cacb/11178780/bfd2ea1a5278/41698_2024_621_Fig2_HTML.jpg

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