School of Computer Science and Engineering Researchers Broaden Understanding of Alzheimer Disease (CirMNet: A Shape-Based Hybrid Feature Extraction Technique Using CNN and CMSMD for Alzheimer's MRI Classification).

Předmět:	ALZHEIMER'S disease COMPUTER engineering COMPUTER science EXTRACTION techniques FEATURE extraction
Zdroj:	Pain & Central Nervous System Week; 6/28/2024, p976-976, 1p
Abstrakt:	Researchers from the School of Computer Science and Engineering have developed a new approach called Circular Mesh Network (CirMNet) for the classification of Alzheimer's disease using MRI scans. The technique combines the strengths of Convolutional Neural Networks (CNNs) and Circular Mesh-based Shape and Margin Descriptor (CMSMD) to extract structural and texture features from the images. The model achieved a high accuracy of 97.34% in classifying different stages of Alzheimer's disease. This research represents a significant improvement over existing methods in the field. [Extracted from the article]
Databáze:	Complementary Index
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