A Study on Various Deep Learning Algorithms to Diagnose Alzheimer’s Disease

  • M. Deepika NairEmail author
  • M. S. Sinta
  • M. Vidya
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)


Alzheimer’s disease (AD) is one of the most frequent types of dementia, which is deterioration in mental ability severe enough to interfere with daily life and gradually affect the human’s brain, its capability to learn, think and communicate. The symptoms of AD develop over time and become a major brain disease over the course of several years. To bring out patterns from the brain neuroimaging data, different statistical and machine learning approaches have been used to find the Alzheimer’s disease present in older adults at clinical as well as research applications; however, differentiating the phases of the Alzheimer’s and healthy brain data has been difficult due to the similarity in brain atrophy patterns and image intensities. Recently, number of deep learning methods has been expeditiously developing into numerous areas, which consist of medical image analysis. This survey gives out the idea of deep learning-based methods which used to differentiate between Alzheimer’s Magnetic Resonance Imaging (MRI) and functional MRI from the normal healthy control data.


Deep learning Alzheimer’s disease MRI fMRI 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science EngineeringVidya Academy of Science and TechnologyThrissurIndia

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