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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 predi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Japanese Society for Magnetic Resonance in Medicine
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10086394/ https://www.ncbi.nlm.nih.gov/pubmed/36697024 http://dx.doi.org/10.2463/mrms.rev.2022-0102 |
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author | Nakaura, Takeshi Kobayashi, Naoki Yoshida, Naofumi Shiraishi, Kaori Uetani, Hiroyuki Nagayama, Yasunori Kidoh, Masafumi Hirai, Toshinori |
author_facet | Nakaura, Takeshi Kobayashi, Naoki Yoshida, Naofumi Shiraishi, Kaori Uetani, Hiroyuki Nagayama, Yasunori Kidoh, Masafumi Hirai, Toshinori |
author_sort | Nakaura, Takeshi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10086394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Japanese Society for Magnetic Resonance in Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-100863942023-04-12 Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging Nakaura, Takeshi Kobayashi, Naoki Yoshida, Naofumi Shiraishi, Kaori Uetani, Hiroyuki Nagayama, Yasunori Kidoh, Masafumi Hirai, Toshinori Magn Reson Med Sci Review 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. Japanese Society for Magnetic Resonance in Medicine 2023-01-26 /pmc/articles/PMC10086394/ /pubmed/36697024 http://dx.doi.org/10.2463/mrms.rev.2022-0102 Text en ©2023 Japanese Society for Magnetic Resonance in Medicine https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
spellingShingle | Review Nakaura, Takeshi Kobayashi, Naoki Yoshida, Naofumi Shiraishi, Kaori Uetani, Hiroyuki Nagayama, Yasunori Kidoh, Masafumi Hirai, Toshinori Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging |
title | Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging |
title_full | Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging |
title_fullStr | Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging |
title_full_unstemmed | Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging |
title_short | Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging |
title_sort | update on the use of artificial intelligence in hepatobiliary mr imaging |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10086394/ https://www.ncbi.nlm.nih.gov/pubmed/36697024 http://dx.doi.org/10.2463/mrms.rev.2022-0102 |
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