REVIEW ON DETECTION OF ALZHEIMER'S DISEASE USING IMAGE PROCESSING AT EARLY STAGE

  • Unique Paper ID: 160832
  • Volume: 10
  • Issue: 1
  • PageNo: 1464-1469
  • Abstract:
  • Personal lifestyle, genetics, and other environmental factors lead to Alzheimer’s disease (AD), which is an irretrievable disease that demolishes the brain’s memory cells gradually. Early detection of AD, which is a significant challenge, is essential for solidifying the patient's quality of life and establishing efficient care along with the targeted medicine. Recently, in predicting AD, Artificial Intelligence (AI)-centric approaches, namely Machine Learning (ML) and Deep Learning (DL) have exhibited great promise. In recent days, for medical staff, there is an inevitable trend for detecting AD in disparate phases by the combination of functional Magnetic Resonance Imaging (fMRI) and AI approaches like DL. The DL algorithm’s human-level performance has been efficiently displayed in disparate disciplines. Hence, this work explains AD, the detection of AD utilizing Image Processing (IP) at an early stage, types of IP modalities utilized for the earlier detection of AD, AI approaches utilized in AD detection at an early stage, and performance comparison of AI approaches utilized in AD detection at an earlier stage.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{160832,
        author = {T SANGEETHA DEVI and Dr V.RAGHAVENDRAN and Dr.M.RAHIMA BEEVI},
        title = {REVIEW ON DETECTION OF ALZHEIMER'S DISEASE USING IMAGE PROCESSING AT EARLY STAGE},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {1},
        pages = {1464-1469},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=160832},
        abstract = {Personal lifestyle, genetics, and other environmental factors lead to Alzheimer’s disease (AD), which is an irretrievable disease that demolishes the brain’s memory cells gradually. Early detection of AD, which is a significant challenge, is essential for solidifying the patient's quality of life and establishing efficient care along with the targeted medicine. Recently, in predicting AD, Artificial Intelligence (AI)-centric approaches, namely Machine Learning (ML) and Deep Learning (DL) have exhibited great promise. In recent days, for medical staff, there is an inevitable trend for detecting AD in disparate phases by the combination of functional Magnetic Resonance Imaging (fMRI) and AI approaches like DL. The DL algorithm’s human-level performance has been efficiently displayed in disparate disciplines. Hence, this work explains AD, the detection of AD utilizing Image Processing (IP) at an early stage, types of IP modalities utilized for the earlier detection of AD, AI approaches utilized in AD detection at an early stage, and performance comparison of AI approaches utilized in AD detection at an earlier stage.},
        keywords = {Alzheimer’s disease, Image processing, Artificial intelligence, Machine learning and Deep learning},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 1
  • PageNo: 1464-1469

REVIEW ON DETECTION OF ALZHEIMER'S DISEASE USING IMAGE PROCESSING AT EARLY STAGE

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