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Updated: Jul 26, 2025

An Experimental Protocol for Assessing the Performance of New Ultrasound Probes Based on CMUT Technology in Application to Brain Imaging
Published on: September 24, 2017
The potential of 'Segment Anything' (SAM) for universal intelligent ultrasound image guidance
Guochen Ning1, Hanyin Liang1, Zhongliang Jiang2
1Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.
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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