论文标题
早期阿尔茨海默氏病检测的MRI图像分析方法
MRI Images Analysis Method for Early Stage Alzheimer's Disease Detection
论文作者
论文摘要
阿尔茨海默氏病是一种神经发生疾病，会改变记忆，认知功能导致死亡。通过检测初步阶段（称为轻度认知障碍（MCI））的早期诊断该疾病仍然是一个具有挑战性的问题。在这方面，我们在本文中介绍了一种强大的分类体系结构，该结构实现了预训练的网络Alexnet，以自动从磁共振成像（MRI）图像中提取最突出的特征，以便在MCI阶段检测阿尔茨海默氏病。使用OASIS数据库大脑的大数据库评估所提出的方法。使用大脑的各个部分：额，矢状和轴向。提出的方法通过使用420个受试者实现了96.83％的精度：210正常和210 MRI
Alzheimer's disease is a neurogenerative disease that alters memories, cognitive functions leading to death. Early diagnosis of the disease, by detection of the preliminary stage, called Mild Cognitive Impairment (MCI), remains a challenging issue. In this respect, we introduce, in this paper, a powerful classification architecture that implements the pre-trained network AlexNet to automatically extract the most prominent features from Magnetic Resonance Imaging (MRI) images in order to detect the Alzheimer's disease at the MCI stage. The proposed method is evaluated using a big database from OASIS Database Brain. Various sections of the brain: frontal, sagittal and axial were used. The proposed method achieved 96.83% accuracy by using 420 subjects: 210 Normal and 210 MRI
