融合人工智能和吲哚青绿荧光成像的新型腹腔镜胆囊切除术导航。

IF 3.2 3区医学 Q2 GASTROENTEROLOGY & HEPATOLOGY

Journal of Hepato‐Biliary‐Pancreatic Sciences Pub Date : 2024-04-01 DOI:10.1002/jhbp.1422

Yoshihiko Tashiro, Takeshi Aoki, Nao Kobayashi, Kodai Tomioka, Kazuhiko Saito, Kazuhiro Matsuda, Tomokazu Kusano

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引用次数: 0

摘要

这项初步研究首次证明，人工智能可以在腹腔镜胆囊切除术和 ICG 荧光胆管造影术中精确识别疏松结缔组织。Tashiro 及其同事总结说，这种融合了人工智能和 ICG 荧光成像的新型实时导航模式可提高安全性，并提供更可靠的腹腔镜或机器人手术。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Novel navigation for laparoscopic cholecystectomy fusing artificial intelligence and indocyanine green fluorescent imaging

查看原文本刊更多论文

Novel navigation for laparoscopic cholecystectomy fusing artificial intelligence and indocyanine green fluorescent imaging

This preliminary study is the first to demonstrate that AI can precisely identify loose connective tissue during laparoscopic cholecystectomy and ICG fluorescent cholangiography. Tashiro and colleagues conclude that this novel real-time navigation modality fusing AI and ICG fluorescent imaging may enhance safety and provide more reliable laparoscopic or robotic surgery.

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来源期刊

Journal of Hepato‐Biliary‐Pancreatic Sciences GASTROENTEROLOGY & HEPATOLOGY-SURGERY

自引率

10.00%

发文量

178

审稿时长

6-12 weeks

期刊介绍： The Journal of Hepato-Biliary-Pancreatic Sciences (JHBPS) is the leading peer-reviewed journal in the field of hepato-biliary-pancreatic sciences. JHBPS publishes articles dealing with clinical research as well as translational research on all aspects of this field. Coverage includes Original Article, Review Article, Images of Interest, Rapid Communication and an announcement section. Letters to the Editor and comments on the journal’s policies or content are also included. JHBPS welcomes submissions from surgeons, physicians, endoscopists, radiologists, oncologists, and pathologists.