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图像预处理方法对MRI放射学特征的影响在帕金森病运动亚型分析中的特征变化和分类性能

Mehdi Panahi¹, Mahboube Sadat Hosseini², Seyyed Mahmoud Reza Aghamiri²

¹Department of Computer Engineering, Payame Noor University Erbil Branch, Erbil, Iraq. mitipanahi@gmail.com.

Scientific reports

|November 14, 2025

概括

选择适当的磁共振成像 (MRI) 预处理方法对于帕金森病 (PD) 运动亚型分类中可重现的放射性特征至关重要. 排除不可重复的特征通常会提高分类的准确性,强调预处理选择的重要性.

科学领域:

神经成像是一种神经成像.
无线电学 (Radiomics) 是一种辐射学.
生物统计学生物统计学

背景情况:

帕金森病 (PD) 运动亚型表现出不同的神经成像模式.
对MRI数据的放射学分析具有区分这些亚型的潜力.
标准化MRI预处理对于可靠的放射性特征提取至关重要.

研究的目的:

评估各种MRI预处理管道对放射性特征可重现性的影响.
评估预处理对PD电机子类型分类性能的影响.
确定最佳的预处理策略,以进行强大的PD放射学分析.

主要方法:

从帕金森病进展标记者倡议 (PPMI) 数据库中分析了210个T1加权的MRI扫描.
五个不同的MRI预处理管道的应用.
从16个大脑区域提取和评估22560个放射性特征,使用类内相关系数 (ICC).
支持矢量机 (SVM) 分类器的开发,以比较具有和没有可复制特征的性能.

主要成果:

基于波形的特征显示出最高的可重现性 (37%与ICC≥0.90).
苏珊无效化+偏差场校正+Z分数规范化管道最初产生了0.88的ROC曲线下的最大面积 (AUC).
排除不可复制的特征显著改善了分类性能,尤其是偏差场校正+Z-score规范化 (AUC从0.49增加到0.64).
纹理特征 (GLCM,GLSZM) 在不同的预处理方法中具有很高的可重现性.

结论:

磁力共振成像预处理显著影响放射性特征的可重现性和PD电机亚型的分类.
基于波纹和纹理的特征提供了高可重现性.
排除不可复制的特征通常会提高分类准确性,强调需要在PD放射学中进行严格的预处理选择和验证.

关键词:

功能可复制性功能可复制性核磁共振成像放射学机器学习分类机器学习分类.发动机子类型发动机子类型帕金森病是帕金森氏症的一种疾病.预加工方法预加工方法

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