Scholarlink

Brain disorders are among the most challenging health issues faced by humanity. These disorders affect the brain’s normal functioning and make patients reliant on caregivers to perform their daily chores. To address this challenge, computer-assisted diagnostic (CAD) systems play a pivotal role in detecting and classifying brain disorders. CAD systems inherently rely on deep learning techniques to accurately identify brain disorders. This review paper aims to provide researchers with comprehensive and relevant information on brain disorders, neuroimaging modalities used, and the deep learning techniques employed in CAD systems to deliver reliable and accurate diagnoses. We reviewed papers from the different databases covering the years 2022 to 2024, selecting 75 papers for review based on parameters such as brain disorders, neuroimaging modalities, CNN models, datasets, and performance metrics. In this review, we focus on four brain disorders: Alzheimer’s disease, Parkinson’s disease, autism spectrum disorder, and schizophrenia. The most significant contribution of this paper is consolidating the findings of papers selected for review, limitations of our review paper and future research directions.

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

Detection and Classification of Brain Disorders Using Neuroimaging Modalities and Deep Learning Techniques: A Systematic Literature Review

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Archana Thakran,
  • Yogesh Kumar Gupta

摘要

Brain disorders are among the most challenging health issues faced by humanity. These disorders affect the brain’s normal functioning and make patients reliant on caregivers to perform their daily chores. To address this challenge, computer-assisted diagnostic (CAD) systems play a pivotal role in detecting and classifying brain disorders. CAD systems inherently rely on deep learning techniques to accurately identify brain disorders. This review paper aims to provide researchers with comprehensive and relevant information on brain disorders, neuroimaging modalities used, and the deep learning techniques employed in CAD systems to deliver reliable and accurate diagnoses. We reviewed papers from the different databases covering the years 2022 to 2024, selecting 75 papers for review based on parameters such as brain disorders, neuroimaging modalities, CNN models, datasets, and performance metrics. In this review, we focus on four brain disorders: Alzheimer’s disease, Parkinson’s disease, autism spectrum disorder, and schizophrenia. The most significant contribution of this paper is consolidating the findings of papers selected for review, limitations of our review paper and future research directions.