Abstract
Modern medical diagnosis equipments included with digital signal processing capabilities have been used for fast and accurate diagnosis of brain structure abnormalities. In this paper a multi resolution based noise removal in magnetic resonance images for abnormality detection and recognition within the brain has been proposed. Wavelet and curvelet based multi resolution approximation has been used to decompose the inter-object relationships into different levels of detail. Contourlet based multi resolution approximation is presented in this work for better abnormality detection. Comparison of extracted feature points between the reference image and the image under study has been made in detection of the abnormality.
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