超声波
盆底
医学
人工智能
计算机科学
医学物理学
放射科
解剖
作者
Xinghua Huang,Yan Wang,Siyin Li,Yang Li,Juan Zhao,Daoning Guo
摘要
Pelvic floor ultrasound provides a clear depiction of pelvic floor structures and their spatial anatomical relationships, enabling enhanced observation of pelvic organ function and position. The integration of artificial intelligence (AI) into medical imaging has revolutionized the automatic analysis of imaging data, offering efficient and accurate preprocessing and analysis. This technological advance addresses challenges associated with traditional pelvic floor ultrasound, such as reliance on operator's experience, time-intensive manual measurements, and significant potential for human error. Current AI applications in pelvic floor ultrasound encompass automatic measurement of the angle of progress (AOP), automatic segmentation of the levator hiatus (LH), and automatic identification of the levator ani muscle (LAM). AI excels in mimicking human analysis, distilling patterns from reorganized data. This paper, grounded in a comprehensive literature review, outlines the principal aspects of pelvic floor ultrasound and its augmentation through AI, highlighting the application value and progress of AI in this field.
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