DIAGNOSIS OF ALZHEIMER’S DISEASE USING WATERSHED TECHNIQUE IN MATLAB
In this research paper, we are proposing an easy and accurate method for effective diagnosis of Alzheimer’s disease by using Watershed’s marker technique in MATLAB. Ultimately, Watershed method leads us to image processing methodology.
As per facts and readings, on average, the diagnosis takes at least 7 years and sometimes, it may also take 14 years. Moreover, much research shows that during the diagnosis of Alzheimer disease, 97 percent of patients die and only 3 percent of patients survive after 14 years of diagnosis. This is mostly because of the late diagnosis and expensive methodology like single photon emission computed tomography used for detection of Alzheimer’s disease. Hence, it is well known that Alzheimer disease is classified as a neurodegenerative disorder. This is the cause and progression of the disease and it is still not well understood; however, it is associated with plaques and tangles caused in the brain.
This research that we are proposing is focused on the method for the diagnosis of Alzheimer’s disease, which is entirely based on image processing using MATLAB and it enables us to acquire fast and robust results. Not only this, it is much cheaper so that the poor can also be able to afford it and it is way better than the old methods which were being implemented. It only needs an MRI image to process and analyzes the Alzheimer’s symptoms based on the color range difference than normal brain image. Selected color schemes can be observed on MATLAB software and functions like; gradient magnitude, grayscale, foreground objects, watershed transform and background markers would be used.
Our research work is based on experimental methodology. The results that we have gathered after our research illustrate much better detection of Alzheimer’s disease and is also able to analyze other diseases like a brain tumor and much more.
Keywords: Alzheimer disease, image processing, watershed technique, MRI image, gradient magnitude, MATLAB
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