A Novel Pre-Processing Approach for the Denoising of Alzheimer Disease Image DatasetAuthor : M. Natarajan and S. Sathiamoorthy
Volume 7 No.2 July-September 2018 pp 107-112
Medical imaging acts an essential part in the domain of medicinal science. In today situation image segmentation is employed to obtain abnormal tissues from healthy tissues naturally in medical images. Noise in an image is annoying to us as it degrades and interrupts the quality of the image. Noise removal is perpetually a problematic task so as edge maintenance at the intensity of the interrupted noise in the real image is essential. Alzheimer’s disease is a neurological dysfunction in which the destruction of brain cells creates cognitive decline and Memory Loss. A neurodegenerative type of dementia, the disease begins mild and becomes progressively severe. A vital area under medical research is Brain image analysis, effects to identify brain diseases. The preeminent causes of Alzheimer’s diseases are blood flow and low brain activity. In this paper, a framework has proposed in the pre-processing of filtering and noise removal in the Alzheimer disease image dataset. This framework optimally balances the level of protection methods according to the noise density.
Image processing, Alzheimer Disease, Pre-processing, Noise removal, Filtering
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