Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Komatsu, Masaaki, Sakai, Akira, Dozen, Ai, Shozu, Kanto, Yasutomi, Suguru, Machino, Hidenori, Asada, Ken, Kaneko, Syuzo, Hamamoto, Ryuji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
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
_version_ 1783726636953239552
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
work_keys_str_mv AT komatsumasaaki towardsclinicalapplicationofartificialintelligenceinultrasoundimaging
AT sakaiakira towardsclinicalapplicationofartificialintelligenceinultrasoundimaging
AT dozenai towardsclinicalapplicationofartificialintelligenceinultrasoundimaging
AT shozukanto towardsclinicalapplicationofartificialintelligenceinultrasoundimaging
AT yasutomisuguru towardsclinicalapplicationofartificialintelligenceinultrasoundimaging
AT machinohidenori towardsclinicalapplicationofartificialintelligenceinultrasoundimaging
AT asadaken towardsclinicalapplicationofartificialintelligenceinultrasoundimaging
AT kanekosyuzo towardsclinicalapplicationofartificialintelligenceinultrasoundimaging
AT hamamotoryuji towardsclinicalapplicationofartificialintelligenceinultrasoundimaging