Scholarlink

Treating Alzheimer’s Disease (AD) and preventing further degeneration are becoming increasingly important. Doctors who could view many morphological aspects for improved clinical practices would evaluate patients more extensively. Previous studies have shown the value of applying deep learning to T1-weighted MRI images to differentiate AD from Normal Control. This paper proposes the classification of three binary classifications by applying 3D CNN Network. A Modified Ant Colony Optimization (MACO) technique is proposed for optimizing the different weights of the network. The effectiveness of the proposed model is assessed by using a sample of 259 ADNI individuals.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Diagnosing the Early Stages of Alzheimer’s Disease by Applying the Modified Ant Colony Optimization Technique

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Rashmi Kumari,
  • Subhranil Das,
  • Raghwendra Kishore Singh

摘要

Treating Alzheimer’s Disease (AD) and preventing further degeneration are becoming increasingly important. Doctors who could view many morphological aspects for improved clinical practices would evaluate patients more extensively. Previous studies have shown the value of applying deep learning to T1-weighted MRI images to differentiate AD from Normal Control. This paper proposes the classification of three binary classifications by applying 3D CNN Network. A Modified Ant Colony Optimization (MACO) technique is proposed for optimizing the different weights of the network. The effectiveness of the proposed model is assessed by using a sample of 259 ADNI individuals.