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Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging
Artificial intelligence (AI) is being increasingly adopted in medical research and applications. Medical AI devices have continuously been approved by the Food and Drug Administration in the United States and the responsible institutions of other countries. Ultrasound (US) imaging is commonly used i...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8301304/ https://www.ncbi.nlm.nih.gov/pubmed/34201827 http://dx.doi.org/10.3390/biomedicines9070720 |
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author | Komatsu, Masaaki Sakai, Akira Dozen, Ai Shozu, Kanto Yasutomi, Suguru Machino, Hidenori Asada, Ken Kaneko, Syuzo Hamamoto, Ryuji |
author_facet | Komatsu, Masaaki Sakai, Akira Dozen, Ai Shozu, Kanto Yasutomi, Suguru Machino, Hidenori Asada, Ken Kaneko, Syuzo Hamamoto, Ryuji |
author_sort | Komatsu, Masaaki |
collection | PubMed |
description | Artificial intelligence (AI) is being increasingly adopted in medical research and applications. Medical AI devices have continuously been approved by the Food and Drug Administration in the United States and the responsible institutions of other countries. Ultrasound (US) imaging is commonly used in an extensive range of medical fields. However, AI-based US imaging analysis and its clinical implementation have not progressed steadily compared to other medical imaging modalities. The characteristic issues of US imaging owing to its manual operation and acoustic shadows cause difficulties in image quality control. In this review, we would like to introduce the global trends of medical AI research in US imaging from both clinical and basic perspectives. We also discuss US image preprocessing, ingenious algorithms that are suitable for US imaging analysis, AI explainability for obtaining informed consent, the approval process of medical AI devices, and future perspectives towards the clinical application of AI-based US diagnostic support technologies. |
format | Online Article Text |
id | pubmed-8301304 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83013042021-07-24 Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging Komatsu, Masaaki Sakai, Akira Dozen, Ai Shozu, Kanto Yasutomi, Suguru Machino, Hidenori Asada, Ken Kaneko, Syuzo Hamamoto, Ryuji Biomedicines Review Artificial intelligence (AI) is being increasingly adopted in medical research and applications. Medical AI devices have continuously been approved by the Food and Drug Administration in the United States and the responsible institutions of other countries. Ultrasound (US) imaging is commonly used in an extensive range of medical fields. However, AI-based US imaging analysis and its clinical implementation have not progressed steadily compared to other medical imaging modalities. The characteristic issues of US imaging owing to its manual operation and acoustic shadows cause difficulties in image quality control. In this review, we would like to introduce the global trends of medical AI research in US imaging from both clinical and basic perspectives. We also discuss US image preprocessing, ingenious algorithms that are suitable for US imaging analysis, AI explainability for obtaining informed consent, the approval process of medical AI devices, and future perspectives towards the clinical application of AI-based US diagnostic support technologies. MDPI 2021-06-23 /pmc/articles/PMC8301304/ /pubmed/34201827 http://dx.doi.org/10.3390/biomedicines9070720 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Komatsu, Masaaki Sakai, Akira Dozen, Ai Shozu, Kanto Yasutomi, Suguru Machino, Hidenori Asada, Ken Kaneko, Syuzo Hamamoto, Ryuji Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging |
title | Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging |
title_full | Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging |
title_fullStr | Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging |
title_full_unstemmed | Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging |
title_short | Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging |
title_sort | towards clinical application of artificial intelligence in ultrasound imaging |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8301304/ https://www.ncbi.nlm.nih.gov/pubmed/34201827 http://dx.doi.org/10.3390/biomedicines9070720 |
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