Journal
BIOMEDICINES
Volume 9, Issue 7, Pages -Publisher
MDPI
DOI: 10.3390/biomedicines9070720
Keywords
ultrasound imaging; artificial intelligence; machine learning; deep learning; preprocessing; classification; detection; segmentation; explainability
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Funding
- Advanced Integrated Intelligence Platform (MEXT)
- commissioned projects income for the RIKEN AIP-FUJITSU Collaboration Center
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This review introduces the global trends of medical AI research in ultrasound imaging, covering challenges such as image quality control, algorithm selection, informed consent, and future prospects for the clinical application of AI technologies.
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.
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