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Application and prospects of AI-based radiomics in ultrasound diagnosis 被引量:1
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作者 Haoyan Zhang Zheling Meng +2 位作者 Jinyu Ru Yaqing Meng Kun Wang 《Visual Computing for Industry,Biomedicine,and Art》 EI 2023年第1期288-303,共16页
Artificial intelligence (AI)-based radiomics has attracted considerable research attention in the field of medical imaging, including ultrasound diagnosis. Ultrasound imaging has unique advantages such as high tempora... Artificial intelligence (AI)-based radiomics has attracted considerable research attention in the field of medical imaging, including ultrasound diagnosis. Ultrasound imaging has unique advantages such as high temporal resolution, low cost, and no radiation exposure. This renders it a preferred imaging modality for several clinical scenarios. This review includes a detailed introduction to imaging modalities, including Brightness-mode ultrasound, color Doppler flow imaging, ultrasound elastography, contrast-enhanced ultrasound, and multi-modal fusion analysis. It provides an overview of the current status and prospects of AI-based radiomics in ultrasound diagnosis, highlighting the application of AI-based radiomics to static ultrasound images, dynamic ultrasound videos, and multi-modal ultrasound fusion analysis. 展开更多
关键词 Radiomics ultrasound imaging Artificial intelligence Deep learning B-mode ultrasound Color Doppler flow imaging ultrasound elastography Contrast-enhanced ultrasound multimodal ultrasound
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