REVIEW ON DETECTION OF ALZHEIMER'S DISEASE USING IMAGE PROCESSING AT EARLY STAGE
Author(s):
T SANGEETHA DEVI, Dr V.RAGHAVENDRAN, Dr.M.RAHIMA BEEVI
Keywords:
Alzheimer’s disease, Image processing, Artificial intelligence, Machine learning and Deep learning
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.
Article Details
Unique Paper ID: 160832

Publication Volume & Issue: Volume 10, Issue 1

Page(s): 1464 - 1469
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