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深度学习在消化系统图像处理中应用的系统评价

A systematic review on application of deep learning in digestive system image processing.

作者信息

Zhuang Huangming, Zhang Jixiang, Liao Fei

机构信息

Gastroenterology Department, Renmin Hospital of Wuhan University, Wuhan, 430060 Hubei China.

出版信息

Vis Comput. 2023;39(6):2207-2222. doi: 10.1007/s00371-021-02322-z. Epub 2021 Oct 31.

Abstract

With the advent of the big data era, the application of artificial intelligence represented by deep learning in medicine has become a hot topic In gastroenterology, deep learning has accomplished remarkable accomplishments in endoscopy, imageology, and pathology. Artificial intelligence has been applied to benign gastrointestinal tract lesions, early cancer, tumors, inflammatory bowel diseases, livers, pancreas, and other diseases. Computer-aided diagnosis significantly improve diagnostic accuracy and reduce physicians' workload and provide a shred of evidence for clinical diagnosis and treatment. In the near future, artificial intelligence will have high application value in the field of medicine. This paper mainly summarizes the latest research on artificial intelligence in diagnosing and treating digestive system diseases and discussing artificial intelligence's future in digestive system diseases. We sincerely hope that our work can become a stepping stone for gastroenterologists and computer experts in artificial intelligence research and facilitate the application and development of computer-aided image processing technology in gastroenterology.

摘要

随着大数据时代的到来,以深度学习为代表的人工智能在医学领域的应用已成为热门话题。在胃肠病学领域,深度学习在内镜检查、影像学和病理学方面取得了显著成就。人工智能已应用于胃肠道良性病变、早期癌症、肿瘤、炎症性肠病、肝脏、胰腺等疾病。计算机辅助诊断显著提高了诊断准确性,减轻了医生的工作量,并为临床诊断和治疗提供了依据。在不久的将来,人工智能在医学领域将具有很高的应用价值。本文主要总结了人工智能在消化系统疾病诊断和治疗方面的最新研究,并探讨了人工智能在消化系统疾病中的未来发展。我们真诚希望我们的工作能够成为胃肠病学家和计算机专家在人工智能研究中的垫脚石,并促进计算机辅助图像处理技术在胃肠病学中的应用和发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56b1/8557108/f21d32b1aaa4/371_2021_2322_Fig1_HTML.jpg

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