Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging
Author:
Affiliation:
1. Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University
Publisher
Japanese Society for Magnetic Resonance in Medicine
Subject
Radiology, Nuclear Medicine and imaging
Link
https://www.jstage.jst.go.jp/article/mrms/22/2/22_rev.2022-0102/_pdf
Reference71 articles.
1. 1. Sakai K, Yamada K. Machine learning studies on major brain diseases: 5-year trends of 2014-2018. Jpn J Radiol 2019; 37:34–72.
2. 2. Nakata N. Recent technical development of artificial intelligence for diagnostic medical imaging. Jpn J Radiol 2019; 37:103–108.
3. 3. Noguchi T, Higa D, Asada T, et al. Artificial intelligence using neural network architecture for radiology (AINNAR): classification of MR imaging sequences. Jpn J Radiol 2018; 36:691–697.
4. 4. Fujioka T, Kubota K, Mori M, et al. Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network. Jpn J Radiol 2019; 37:466–472.
5. 5. Jiang D, Dou W, Vosters L, Xu X, Sun Y, Tan T. Denoising of 3D magnetic resonance images with multi-channel residual learning of convolutional neural network. Jpn J Radiol 2018; 36:566–574.
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Early Beginnings of AI;Advances in Business Information Systems and Analytics;2024-05-17
2. Low tube voltage and deep-learning reconstruction for reducing radiation and contrast medium doses in thin-slice abdominal CT: a prospective clinical trial;European Radiology;2024-05-16
3. Evaluation and Prediction of Post-Hepatectomy Liver Failure Using Imaging Techniques: Value of Gadoxetic Acid-Enhanced Magnetic Resonance Imaging;Korean Journal of Radiology;2024
4. Fairness of artificial intelligence in healthcare: review and recommendations;Japanese Journal of Radiology;2023-08-04
5. Clinical applications of artificial intelligence in liver imaging;La radiologia medica;2023-05-10
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3