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Ultrasound-based artificial intelligence in gastroenterology and hepatology
Artificial intelligence (AI), especially deep learning, is gaining extensive attention for its excellent performance in medical image analysis. It can automatically make a quantitative assessment of complex medical images and help doctors to make more accurate diagnoses. In recent years, AI based on...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9594013/ https://www.ncbi.nlm.nih.gov/pubmed/36304086 http://dx.doi.org/10.3748/wjg.v28.i38.5530 |
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author | Liu, Ji-Qiao Ren, Jia-Yu Xu, Xiao-Lan Xiong, Li-Yan Peng, Yue-Xiang Pan, Xiao-Fang Dietrich, Christoph F Cui, Xin-Wu |
author_facet | Liu, Ji-Qiao Ren, Jia-Yu Xu, Xiao-Lan Xiong, Li-Yan Peng, Yue-Xiang Pan, Xiao-Fang Dietrich, Christoph F Cui, Xin-Wu |
author_sort | Liu, Ji-Qiao |
collection | PubMed |
description | Artificial intelligence (AI), especially deep learning, is gaining extensive attention for its excellent performance in medical image analysis. It can automatically make a quantitative assessment of complex medical images and help doctors to make more accurate diagnoses. In recent years, AI based on ultrasound has been shown to be very helpful in diffuse liver diseases and focal liver lesions, such as analyzing the severity of nonalcoholic fatty liver and the stage of liver fibrosis, identifying benign and malignant liver lesions, predicting the microvascular invasion of hepatocellular carcinoma, curative transarterial chemoembolization effect, and prognoses after thermal ablation. Moreover, AI based on endoscopic ultrasonography has been applied in some gastrointestinal diseases, such as distinguishing gastric mesenchymal tumors, detection of pancreatic cancer and intraductal papillary mucinous neoplasms, and predicting the preoperative tumor deposits in rectal cancer. This review focused on the basic technical knowledge about AI and the clinical application of AI in ultrasound of liver and gastroenterology diseases. Lastly, we discuss the challenges and future perspectives of AI. |
format | Online Article Text |
id | pubmed-9594013 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-95940132022-10-26 Ultrasound-based artificial intelligence in gastroenterology and hepatology Liu, Ji-Qiao Ren, Jia-Yu Xu, Xiao-Lan Xiong, Li-Yan Peng, Yue-Xiang Pan, Xiao-Fang Dietrich, Christoph F Cui, Xin-Wu World J Gastroenterol Minireviews Artificial intelligence (AI), especially deep learning, is gaining extensive attention for its excellent performance in medical image analysis. It can automatically make a quantitative assessment of complex medical images and help doctors to make more accurate diagnoses. In recent years, AI based on ultrasound has been shown to be very helpful in diffuse liver diseases and focal liver lesions, such as analyzing the severity of nonalcoholic fatty liver and the stage of liver fibrosis, identifying benign and malignant liver lesions, predicting the microvascular invasion of hepatocellular carcinoma, curative transarterial chemoembolization effect, and prognoses after thermal ablation. Moreover, AI based on endoscopic ultrasonography has been applied in some gastrointestinal diseases, such as distinguishing gastric mesenchymal tumors, detection of pancreatic cancer and intraductal papillary mucinous neoplasms, and predicting the preoperative tumor deposits in rectal cancer. This review focused on the basic technical knowledge about AI and the clinical application of AI in ultrasound of liver and gastroenterology diseases. Lastly, we discuss the challenges and future perspectives of AI. Baishideng Publishing Group Inc 2022-10-14 2022-10-14 /pmc/articles/PMC9594013/ /pubmed/36304086 http://dx.doi.org/10.3748/wjg.v28.i38.5530 Text en ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https: //creativecommons.org/Licenses/by-nc/4.0/ |
spellingShingle | Minireviews Liu, Ji-Qiao Ren, Jia-Yu Xu, Xiao-Lan Xiong, Li-Yan Peng, Yue-Xiang Pan, Xiao-Fang Dietrich, Christoph F Cui, Xin-Wu Ultrasound-based artificial intelligence in gastroenterology and hepatology |
title | Ultrasound-based artificial intelligence in gastroenterology and hepatology |
title_full | Ultrasound-based artificial intelligence in gastroenterology and hepatology |
title_fullStr | Ultrasound-based artificial intelligence in gastroenterology and hepatology |
title_full_unstemmed | Ultrasound-based artificial intelligence in gastroenterology and hepatology |
title_short | Ultrasound-based artificial intelligence in gastroenterology and hepatology |
title_sort | ultrasound-based artificial intelligence in gastroenterology and hepatology |
topic | Minireviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9594013/ https://www.ncbi.nlm.nih.gov/pubmed/36304086 http://dx.doi.org/10.3748/wjg.v28.i38.5530 |
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