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一个基于模糊认知地图的框架用于阿尔茨海默病的诊断,使用多模式磁共振成像-正子发射断层扫描注册

Seyed Assef Mahdavi¹, Keivan Maghooli², Fardad Farokhi¹

¹Department of Biomedical Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

Journal of medical signals and sensors

|November 17, 2025

概括

这项研究开发了一种针对阿尔茨海默病 (AD) 的新型计算机辅助诊断系统. 将模糊认知地图 (FCM) 与神经成像数据集成,实现了早期AD检测93.71%的准确性.

科学领域:

神经成像是一种神经成像.
人工智能的人工智能
医学诊断医学诊断医学诊断

背景情况:

阿尔茨海默病 (AD) 是一种进展性神经退行性疾病,影响记忆和认知.
早期和准确的AD诊断对于患者的管理和治疗至关重要.
结构磁共振成像 (sMRI) 和正子发射断层扫描 (PET) 是AD诊断的关键神经成像工具.

研究的目的:

为阿尔茨海默病引入一种新的计算机辅助诊断系统.
通过整合多模式神经成像数据 (sMRI和PET) 来提高诊断准确性.
评估模糊认知地图 (FCM) 与其他AD诊断分类器的性能.

主要方法:

使用了阿尔茨海默病神经成像计划 (ADNI) 数据集.
使用FSL和SPM分别预处理的sMRI和PET图像.
融合了sMRI和PET的特征,通过自动编码器减少了维度,并使用FCM,SVM,k-NN和MLP进行分类.

主要成果:

基于模糊认知地图 (FCM) 的方法实现了最高的诊断准确率93.71%.
FCM的性能优于支持矢量机,k-最近邻居和多层感知子分类器.
综合系统在对阿尔茨海默病的分类方面表现出卓越的表现.

结论:

将模糊认知地图 (FCM) 与多式神经成像数据集成在AD诊断中是有效的.
拟议的系统显示了改善阿尔茨海默病早期和可靠检测的巨大潜力.
这种方法为推进阿尔茨海默病诊断工具提供了一个有希望的途径.

关键词:

阿尔茨海默氏症是阿尔茨海默氏症的疾病自动编码器自动编码器诊断诊断诊断诊断诊断诊断模糊的认知地图.磁共振成像-正子发射断层扫描.

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