BioScience Trends
Online ISSN : 1881-7823
Print ISSN : 1881-7815
ISSN-L : 1881-7815
Correspondence
The potential of 'Segment Anything' (SAM) for universal intelligent ultrasound image guidance
Guochen NingHanyin LiangZhongliang JiangHui ZhangHongen Liao
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JOURNAL FREE ACCESS

2023 Volume 17 Issue 3 Pages 230-233

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Abstract

Ultrasound image guidance is a method often used to help provide care, and it relies on accurate perception of information, and particularly tissue recognition, to guide medical procedures. It is widely used in various scenarios that are often complex. Recent breakthroughs in large models, such as ChatGPT for natural language processing and Segment Anything Model (SAM) for image segmentation, have revolutionized interaction with information. These large models exhibit a revolutionized understanding of basic information, holding promise for medicine, including the potential for universal autonomous ultrasound image guidance. The current study evaluated the performance of SAM on commonly used ultrasound images and it discusses SAM's potential contribution to an intelligent image-guided framework, with a specific focus on autonomous and universal ultrasound image guidance. Results indicate that SAM performs well in ultrasound image segmentation and has the potential to enable universal intelligent ultrasound image guidance.

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© 2023 International Research and Cooperation Association for Bio & Socio-Sciences Advancement
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