Improved Brain MRI Segmentation for Early Detection of Alzheimer's Disease using Overlaying Analysis and Thresholding

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Alzheimer's disease (AD) with memory loss and cognitive decline as symptoms of the neuro-degenerative condition, damages the brain. The novel approach is proposed for detecting regions of the brain affected by AD using overlaying analysis and thresholding techniques. The current overlaying analysis methods lack accurate thresholding, which leads to a loss of pixel data, indicating highly varied segregation of brain regions. The usage of efficiently identifying disparities in pixel values between multiple digital images through computational analysis is highlighted in the proposed work. We also discuss the challenges and limitations of current image analysis methods, including issues related to misaligned scans and under-thresholding. A new function to find absolute pixel differences on brain Magnetic Resonance Imaging (MRI) scans, segregate the brain into multiple affected regions, and identify those affected by Very Mild Dementia Alzheimer's is applied. The segregated regions are then overlapped and compared with healthy brain regions to observe differences in structural and functional properties. The approach can accurately identify affected regions of the brain and provide valuable information for the diagnosis and prognosis of AD. The model contributes to the ongoing efforts to develop effective and non-invasive methods for detecting and tracking the progression of AD and highlights the potential of observing MRI scan differences using overlapping analysis as a powerful tool in neuroimaging research.

Original languageEnglish
Title of host publication2023 IEEE 4th Annual Flagship India Council International Subsections Conference
Subtitle of host publicationComputational Intelligence and Learning Systems, INDISCON 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350333558
DOIs
Publication statusPublished - 2023
Event4th IEEE Annual Flagship India Council International Subsections Conference, INDISCON 2023 - Mysore, India
Duration: 05-08-202307-08-2023

Publication series

Name2023 IEEE 4th Annual Flagship India Council International Subsections Conference: Computational Intelligence and Learning Systems, INDISCON 2023

Conference

Conference4th IEEE Annual Flagship India Council International Subsections Conference, INDISCON 2023
Country/TerritoryIndia
CityMysore
Period05-08-2307-08-23

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Computational Mathematics
  • Control and Optimization
  • Health Informatics

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