Multilayer classification based Alzheimer's disease detection

Title

Multilayer classification based Alzheimer's disease detection

Creator

Vijayalakshmi S.; Sivakumar V.; Savita; Shukla M.

Description

Hippocampus, a small brain region plays a role in the initiation of the neurodegenerative pathways that leadto Alzheimer's. Humans with MCI are probable to develop Alzheimer's disorder. Hippocampal volume has been proven to indicate which patients with MCI will later develop Alzheimer's. Brain degeneration in MCI progresses over time and varies from person - to - person, making early detection difficult. Magnetic resonance imaging is a tool in diagnosing clinically suspected Alzheimer's disease. Information about the historical development of structural changes as the disease progresses from preclinical to overt stages is shaping understanding of the disease, and also guides diagnosis and treatment decisions in the future. In this study, we developed a new multilayer classification method to identify Alzheimer's disease from brain MRI using contour model and multilayer classifier. This method is evaluated on 436 samples of OASIS dataset and achieved accuracy of method is 93.75 %. 2024 Author(s).

Source

AIP Conference Proceedings, Vol-3161, No. 1

Date

2024-01-01

Publisher

American Institute of Physics

Coverage

Vijayalakshmi S., Department of Data Science, CHRIST University, Lavasa, Pune, India; Sivakumar V., Asia Pacific University of Technology and Innovation (APU), Kuala Lumpur, Malaysia; Savita, School of Engineering and Technology, Maharishi University of Information Technology, Noida, India; Shukla M., School of Engineering and Technology, Maharishi University of Information Technology, Noida, India

Rights

Restricted Access

Relation

ISSN: 0094243X

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1063/5.0229490

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203997863&doi=10.1063%2f5.0229490&partnerID=40&md5=d466c2df3fd6c2eccd4a4289fa03a16b