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Processing MRI brain image using OpenMP and fast filters for noise reduction

Abstract:

The medical diagnosis of most pathologists requires the analysis of the image studies. Therefore, it is important to get the best quality of the images without noise and highlight the details of tissues. The principal aim of this work is to apply different algorithms and filters to reduce the noise of magnetic resonance brain images, due to the noise in these can cause to give a difficult diagnosis. The algorithms considered in this work are the fast mean filter, fast Gaussian filter, and fast median filter; also was used parallel programming in OpenMP. The results show that the parallel implementation of algorithms has more performance in the time processing, localization, and noise reduction than sequential and classic implementation.