模拟剂量降低对人工智能在胸部X射线图中的表现的影响
Hendrik Erenstein1,2,3, Wim P Krijnen3,4, Annemieke van der Heij-Meijer1
1Department of Medical Imaging and Radiation Therapy, Hanze University of Applied Sciences, 9714 CA Groningen, The Netherlands.
Journal of imaging
|March 26, 2025
概括
降低胸部X射线图中的辐射剂量对人工智能 (AI) 模型的性能影响最小,即使图像质量有显著的降低. 患者定位对人工智能预测的影响比模拟剂量减少更大.
科学领域:
- 医学成像医学成像
- 放射学中的人工智能
- 放射学 放射学 放射学 放射学
背景情况:
- 胸部成像对于患者的查和监测至关重要.
- 人工智能 (AI) 模型越来越多地用于支持胸部放射学诊断任务.
- 减少辐射剂量和图像质量对AI性能的影响在很大程度上仍未被探索.
研究的目的:
- 为了模拟低剂量胸部X射线图像.
- 评估模拟剂量降低对卷积神经网络 (CNN) 性能的影响.
- 为了比较剂量减少与患者定位对AI模型预测的影响.
主要方法:
- 训练了14个CNN模型,使用两个空间分辨率的MIMIC数据集中的七个病理标签.
- 在原始,50%和75%低剂量模拟图像上测试模型.
- 使用DeLong测试,根据性别和患者位置分析结果,比较接收器操作者特征 (AUROC) 曲线下的区域.
主要成果:
- 模拟剂量减少的AUROC的平均绝对变化为<0.005,最大变化为0.014.
- 在28个测试组中,在6个测试组中观察到AUROC的显著差异.
- 患者定位对CNN的表现产生了比模拟剂量减少更大的影响.
结论:
- 胸部X射线图中的模拟剂量降低对CNN性能具有最小的临床影响.
- 虽然在某些情况下存在统计学上显著的差异,但剂量降低的整体效果是微不足道的.
- 患者的定位是影响AI在胸部放射学中的表现的更关键因素,而不是减少辐射剂量.
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