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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...

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Autores principales: Nakaura, Takeshi, Kobayashi, Naoki, Yoshida, Naofumi, Shiraishi, Kaori, Uetani, Hiroyuki, Nagayama, Yasunori, Kidoh, Masafumi, Hirai, Toshinori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japanese Society for Magnetic Resonance in Medicine 2023
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.
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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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