1. Dr. RAMESH T. PRAJAPATI - HOD & Associate Professor in CE/IT, Shree Swaminarayan Institute of Technology, Bhat, Gandhinagar,
Gujarat, India.
2. BHAVESH JAIN - Assistant Professor in CE, Indrashil University, Rajpur, Kadi, Gujarat, India.
3. DARSHAN SOLANKI - Assistant Professor in CE, Indrashil University, Rajpur, Kadi, Gujarat, India.
4. KAMLESHSINGH DHANUK - Assistant Professor in CE, Indrashil University, Rajpur, Kadi, Gujarat, India.
5. NIRAJKUMAR THAKOR - Assistant Professor in CE, Indrashil University, Rajpur, Kadi, Gujarat, India.
6. KHUSHBU KHAMAR - Assistant Professor in CE, Indrashil University, Rajpur, Kadi, Gujarat, India.
7. Dr. HITESH H. WANDRA - Principal, Shree Swaminarayan Institute of Technology, Bhat, Gandhinagar, Gujarat, India.
Hippocampus region of the brain is one of the first involved regions inAlzheimer's disease (AD) and mild cognitive impairment (MCI), a prodromal stages of AD. Since the change of hippocampal volume is a defined biomarker for Alzheimer's disease, hippocampus segmentation of brain image can be used to assist the diagnosis of Alzheimer's disease. In this paper, the segmentation of the hippocampus region from brain Magnetic Resonance Images (MRI) is per- formed for the diagnosis of Alzheimer’s disease with help of different machine learning based image segmentation techniques. The database images are obtainedand processed using Histogram Equalization for enhancement. The hippocampus region is located and segmented from the processed brain MRI image using different image segmentation techniques. Then, the segmented image is compared with the ground truth image using image quality parameters. With the help of theparameters, the efficient technique for the segmentation of the hippocampus region, a biomarker for diagnosis of AD.
Alzheimer’s disease, Hippocampus region, Magnetic ResonanceImaging, Machine learning.