Review on Early Detection of Alzheimer’s Disease using Neuroimaging Techniques

Authors

  • Vishnu N Dept. of ECE, BNM Institute of Technology, Bangalore, India
  • Rachana R Vaidya Dept. of ECE, BNM Institute of Technology, Bangalore, India
  • Chaitra N BNM Institute of Technology, Bangalore
  • Srinidhi S P Dept. Of CSE, BNM Institute of Technology, Bangalore, India
  • Shreyas B Dept. Of CSE, BNM Institute of Technology, Bangalore, India

DOI:

https://doi.org/10.5281/zenodo.4420081

Keywords:

Alzheimer’s Disease, Machine Learning, SVM, Neuroimaging Techniques, MRI, SPECT, PET

Abstract

Alzheimer’s disease (AD) is the most common form of dementia. AD begins slowly, where it first involves a part of the brain that controls thought, memory, and language. Names and incidents are things that initial stage AD patients have a hard time remembering. Early detection of AD is very crucial for further aid and treatment. This paper presents a review and analysis of the different methods employed to detect AD or mild cognitive impairment (MCI). Machine learning, neuroimaging, and deep learning neural networks are few of the techniques which are compared and analysed based on their performance and accuracy. Each model is critically analysed and provided with limitations, advantages, and best application.

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References

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Published

2021-01-05

How to Cite

[1]
V. N, R. R. Vaidya, C. N, S. S. P, and S. B, “Review on Early Detection of Alzheimer’s Disease using Neuroimaging Techniques”, pices, vol. 4, no. 9, pp. 215-221, Jan. 2021.

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