Author(s):
Chandni Naidu, Dhanush Kumar, N Maheswari, M Sivagami
Email(s):
chandninaidu@gmail.com , dannykumar.kumar2@gmail.com , maheswari.n@vit.ac.in , msivagami@vit.ac.in
DOI:
10.5958/0974-360X.2018.00977.0 
Address:
Chandni Naidu, Dhanush Kumar, N Maheswari*, M Sivagami
SCSE, Vellore Institute of Technology, Chennai Campus
*Corresponding Author
Published In:
Volume - 11,
Issue - 12,
Year - 2018
ABSTRACT:
Alzheimer’s Disease (AD) is a chronic neuro degenerative disease and its detection in early stage is difficult. Experienced doctors always recommend MRI scans as the first step towards diagnosis. Automating AD’s detection process will help fasten the prediction process. A new technique has been proposed to predict the Alzheimer’s disease. The proposed technique segments the image using marker controlled watershed segmentation with top hat transformation and applies the threshold on the image to extract the hippocampus region of the brain. Threshold value has been set for Alzheimer’s Disease using Open Access Series of Imaging Studies (OASIS) database. The efficiency of the proposed work has been shown with the result of the Alzheimer’s disease prediciton using OASIS dataset.
Cite this article:
Chandni Naidu, Dhanush Kumar, N Maheswari, M Sivagami. Prediction of Alzheimer’s Disease using Brain Images. Research J. Pharm. and Tech 2018; 11(12): 5365-5368. doi: 10.5958/0974-360X.2018.00977.0
Cite(Electronic):
Chandni Naidu, Dhanush Kumar, N Maheswari, M Sivagami. Prediction of Alzheimer’s Disease using Brain Images. Research J. Pharm. and Tech 2018; 11(12): 5365-5368. doi: 10.5958/0974-360X.2018.00977.0 Available on: https://rjptonline.org/AbstractView.aspx?PID=2018-11-12-26