Abstract
EARLY DETECTION OF ALZHEIMER’S DISEASE USING HYBRID SEGMENTATION TECHNIQUE AND TEXTURAL ANALYSIS FROM MRI IMAGES

Asmita Ray, Debnath Bhattacharyya and Prof. Samir Kumar Bandyopadhyay*

ABSTRACT

Alzheimer‟s disease (AD) is the most common form of dementia, early detection is the most essential step for providing the quality of treatment as life span can be increased and eventually brain research can be benefited with monitoring its effectiveness. Magnetic Resonance Imaging (MRI) technique is mostly used as the diagnosis tool of Alzheimer‟s disease. A new approach has been developed in this paper for earlier diagnosis of Alzheimer‟s disease from MRI. The proposed method is carried out in three phases. They are pre-processing, segmentation and feature extraction. In the first phase noise and artifacts have been removed. In the second phase, region affected by the Alzhaimer disease is segmented. In the third phase, affected portion is characterized by the Gray Level Co-occurrance Matrix (GLCM). This paper presents a framework of self- constructed algorithm for detection of AD at an early stage.

Keywords: Alzheimer?s disease, Dementia, Magnetic resonance imaging, Gray level co-occurrence matrix (GLCM).


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