{"title":"人工智能在肝胆磁共振成像中的最新应用。","authors":"Takeshi Nakaura, Naoki Kobayashi, Naofumi Yoshida, Kaori Shiraishi, Hiroyuki Uetani, Yasunori Nagayama, Masafumi Kidoh, Toshinori Hirai","doi":"10.2463/mrms.rev.2022-0102","DOIUrl":null,"url":null,"abstract":"<p><p>The application of machine learning (ML) and deep learning (DL) in radiology has expanded exponentially. In recent years, an extremely large number of studies have reported about the hepatobiliary domain. Its applications range from differential diagnosis to the diagnosis of tumor invasion and prediction of treatment response and prognosis. Moreover, it has been utilized to improve the image quality of DL reconstruction. However, most clinicians are not familiar with ML and DL, and previous studies about these concepts are relatively challenging to understand. In this review article, we aimed to explain the concepts behind ML and DL and to summarize recent achievements in their use in the hepatobiliary region.</p>","PeriodicalId":18119,"journal":{"name":"Magnetic Resonance in Medical Sciences","volume":"22 2","pages":"147-156"},"PeriodicalIF":2.5000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/b2/a3/mrms-22-147.PMC10086394.pdf","citationCount":"0","resultStr":"{\"title\":\"Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging.\",\"authors\":\"Takeshi Nakaura, Naoki Kobayashi, Naofumi Yoshida, Kaori Shiraishi, Hiroyuki Uetani, Yasunori Nagayama, Masafumi Kidoh, Toshinori Hirai\",\"doi\":\"10.2463/mrms.rev.2022-0102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The application of machine learning (ML) and deep learning (DL) in radiology has expanded exponentially. In recent years, an extremely large number of studies have reported about the hepatobiliary domain. Its applications range from differential diagnosis to the diagnosis of tumor invasion and prediction of treatment response and prognosis. Moreover, it has been utilized to improve the image quality of DL reconstruction. However, most clinicians are not familiar with ML and DL, and previous studies about these concepts are relatively challenging to understand. In this review article, we aimed to explain the concepts behind ML and DL and to summarize recent achievements in their use in the hepatobiliary region.</p>\",\"PeriodicalId\":18119,\"journal\":{\"name\":\"Magnetic Resonance in Medical Sciences\",\"volume\":\"22 2\",\"pages\":\"147-156\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/b2/a3/mrms-22-147.PMC10086394.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Magnetic Resonance in Medical Sciences\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2463/mrms.rev.2022-0102\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/1/26 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Magnetic Resonance in Medical Sciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2463/mrms.rev.2022-0102","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/26 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
摘要
机器学习(ML)和深度学习(DL)在放射学中的应用呈指数级增长。近年来,有关肝胆领域的研究报告非常多。其应用范围从鉴别诊断到肿瘤侵犯诊断以及治疗反应和预后预测。此外,它还被用于提高 DL 重建的图像质量。然而,大多数临床医生对 ML 和 DL 并不熟悉,以往关于这些概念的研究也相对难以理解。在这篇综述文章中,我们旨在解释 ML 和 DL 背后的概念,并总结它们在肝胆区域应用的最新成果。
Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging.
The application of machine learning (ML) and deep learning (DL) in radiology has expanded exponentially. In recent years, an extremely large number of studies have reported about the hepatobiliary domain. Its applications range from differential diagnosis to the diagnosis of tumor invasion and prediction of treatment response and prognosis. Moreover, it has been utilized to improve the image quality of DL reconstruction. However, most clinicians are not familiar with ML and DL, and previous studies about these concepts are relatively challenging to understand. In this review article, we aimed to explain the concepts behind ML and DL and to summarize recent achievements in their use in the hepatobiliary region.
期刊介绍:
Magnetic Resonance in Medical Sciences (MRMS or Magn
Reson Med Sci) is an international journal pursuing the
publication of original articles contributing to the progress
of magnetic resonance in the field of biomedical sciences
including technical developments and clinical applications.
MRMS is an official journal of the Japanese Society for
Magnetic Resonance in Medicine (JSMRM).