DIGITAL IMAGE PROCESSING BASED DETECTION OF BRAIN ABNORMALITY FOR ALZHEIMER’S DISEASE
Alzheimer’s disease is a neurological disease. Because of these disease the neuron’s structure are deformed or damaged. The main cause of Alzheimer’s disease is dementia. Due to Alzheimer’s disease several of brain tissues are damaged due to which the memory of patient is going to loss and patient also loses his ability of doing simple tasks. And the damaged in tissues will not be cured. Therefore we call this a neurological disease which is not cured by doctors and due to which the damages of tissues will increases with time. The doctors are able to slow down the progress of this disease. In this paper, a method has been proposed for the detection of Alzheimer’s disease by using the digital image processing. In this case the detection of Alzheimer ‘s disease is based on different features .The data used in this study is provided by the official website of MATHWORKS .In the dataset author had a set of MR images of a patient’s brain scan . This dataset is in form of dicom images .For detection process firstly author used the segmentation process for detecting the ROI, then author measure the volume of gray matter and white matter and cerebrospinal fluid and then author calculate the ratio of gray matter volume to cerebrospinal fluid volume and the ratio of white matter volume to cerebrospinal fluid volume and compare these ratio with the volume of normal brain .After applying the whole process author came to know, is the patient is normal or effected by Alzheimer ‘s disease .