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Analysis and Diagnosis of Dementia Disorder Using Deep Learning Methods: A Comprehensive Review


D. Kavitha and Dr.A. Murugan
Abstract

The dementia is a worldwide concern and early discovery of dementia is substantial for the administration of illness. The facts acquired from Magnetic reverberation imaging (MRI), Positron Emission Tomography (PET) and Computed tomography (CT) have been utilized for the identification of dementia which is testing. Albeit numerous examinations have applied AI techniques for computer aided diagnosis (CAD) of dementia and it is seen that deep learning calculations can be utilized as a successful answer for the equivalent. Deep learning calculations utilize white issue volumes, dark issue volumes, cortical surface zone, cortical thickness, and various kinds of Fractal Brownian Motion co-event networks for surface as highlights to characterize the diverse sort of dementia, for example, Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI). Various investigated deep learning calculations and the best in class techniques executed to determine about dementia.

Volume 12 | Issue 7

Pages: 363-371

DOI: 10.5373/JARDCS/V12I7/20202017