用计算机视觉自动测阴茎弯曲角度，诊断勃起功能障碍更准更快
AI enhanced diagnosis of Peyronies disease a novel approach using Computer Vision
- 通过关键点检测分析图像视频，自动计算弯曲角度
- 灵敏度96.7%，特异性100%，优于传统测量方法
- 非侵入式诊断，适合临床快速筛查与随访
本研究提出一种新型人工智能辅助诊断工具，用于评估勃起功能障碍（Peyronie's Disease, PD），该病全球患病率在0.3%至13.1%之间。方法基于图像与视频的关键点检测，利用先进计算机视觉技术测量阴茎弯曲角度，可精准识别解剖标志点，经与传统量角器测量对比验证。传统诊断依赖主观且侵入性手段，常引发患者不适并导致误差。本方法提供精确、可靠、无创的诊断方案，对区分PD与正常生理变化的敏感度达96.7%，特异性达100%，显著提升泌尿科诊疗效率与患者体验。
原文摘要 · Abstract (English)
This study presents an innovative AI-driven tool for diagnosing Peyronie's Disease (PD), a condition that affects between 0.3% and 13.1% of men worldwide. Our method uses key point detection on both images and videos to measure penile curvature angles, utilizing advanced computer vision techniques. This tool has demonstrated high accuracy in identifying anatomical landmarks, validated against conventional goniometer measurements. Traditional PD diagnosis often involves subjective and invasive methods, which can lead to patient discomfort and inaccuracies. Our approach offers a precise, reliable, and non-invasive diagnostic tool to address these drawbacks. The model distinguishes between PD and normal anatomical changes with a sensitivity of 96.7% and a specificity of 100%. This advancement represents a significant improvement in urological diagnostics, greatly enhancing the efficacy and convenience of PD assessment for healthcare providers and patients.
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