• ABDUL MUMEETH
• TIPPU SULTAN
• MOHAMMAD ZAKWAN JALEEL
• SYED AFAAN
• PROF SHARAVANA K

Alzheimer's disease is a neurological disorder in which the death of brain cells causes memory loss and cognitive decline. A neuro degenerative type of dementia, the disease starts mild and gets progressively worse. An important area under medical research is brain image analysis, results to detect brain diseases. The main causes for alzheimer's diseases is low brain activity and blood flow. In general segmentation technique is using for the medical images .one of the important component of the brain is hippocampus. The normal behavior of human beings is depends on the functionality of hippocampus. Manual segmentation by a specialist on the hippocampus takes many hours. In image processing there are various techniques available for segmentation process. In this paper we implement Deep learning algorithms. The brain hippocampus images converted into binary form using two approaches. The first approach is block mean, mask and labeling concepts and in the second approach top hat, mask and labeling concepts. We implement deep learning techniques to obtain better results in detection of the Alzheimer’s . The shape analysis of hippocampus structure will result in classifying the alzheimer's disease.

"Alzheimer detection ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 7, page no.d407-d411, July-2022, Available :http://www.jetir.org/papers/JETIR2207352.pdf

"Alzheimer detection ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 7, page no. ppd407-d411, July-2022, Available at : http://www.jetir.org/papers/JETIR2207352.pdf