基于ViT的面部诊断图像分析用于精神分裂症检测
Huilin Liu1, Runmin Cao2, Songze Li2,3
1School of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Brain sciences
|January 24, 2025
概括
这项研究引入了一种新的非侵入性方法,用于检测精神分裂症 (SZ),使用面部图像和传统中医的原则. 这种方法提高了诊断的准确性和可解释性,为传统的大脑成像技术提供了更有效的替代方案.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 传统中国医药 传统中国医药
背景情况:
- 目前的精神分裂症 (SZ) 检测依赖于耗时的脑电图和MRI扫描,影响患者的合作和诊断透明度.
- 现有的方法缺乏解释性,这使得临床医生很难理解检测决策的基础.
研究的目的:
- 开发一种使用面部图像检测精神分裂症的非侵入性,高效和可解释的方法.
- 为了利用传统中医的原则,提高SZ诊断.
- 改善患者遵守和临床医生在精神分裂症检测方面的理解.
主要方法:
- 使用视觉变压器 (ViT) 分析面部诊断图像以检测精神分裂症.
- 开发了一种可视化面部特征分布的方法,并量化面部区域的重要性.
- 创建了一个具有921个图像,6个方法和4个评估指标的基准测试平台.
主要成果:
- 与基准方法相比,拟议的方法实现了对精神分裂症检测的准确性提高3-10%.
- 确定了面部区域对于SZ检测至关重要,眼睛,嘴巴和额头是最重要的.
- 结果与中国传统医学的诊断经验一致.
结论:
- 这种新的方法有效地使用面部图像分析来检测精神分裂症,提供了显著的解释性和可视化.
- 这种方法代表了精神分裂症检测的新途径,并为精神疾病研究提供了新的工具.
- 这些发现支持将人工智能驱动的面部分析与传统诊断原则相结合.
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