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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...

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Autores principales: Liu, Ji-Qiao, Ren, Jia-Yu, Xu, Xiao-Lan, Xiong, Li-Yan, Peng, Yue-Xiang, Pan, Xiao-Fang, Dietrich, Christoph F, Cui, Xin-Wu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2022
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.
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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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