摘要
由于相似的大脑模式和像素强度,需要具有高度鉴别性特征表示来进行分类,因此诊断老年人阿尔茨海默病相当困难。本文针对阿尔茨海默病的稳定型与进展型轻度认知障碍识别中使用ResNet进行分析,重点就网络经过优化后如何使其分类效果得到显著提升提出了具体建议。
Due to similar brain patterns and pixel intensities,highly identifiable features are required for classification,hence,it is rather difficult to diagnose Alzheimer’s disease of the elderly.This article analyzes the application of ResNet in the recognition of stable and progressive mild cognitive impairment of Alzheimer’s disease,focusing on how to significantly improve the classification effect of the network after optimization.
作者
丘致榕
Qiu Zhirong(Fujian Normal University,Fuzhou 350001)
出处
《中阿科技论坛（中英文）》
2021年第4期128-130,共3页
China-Arab States Science and Technology Forum
