project report on brain MRI image detection of abnormalities and classification
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 i would like to get details on project report on brain MRI image detection of abnormalities and classification ..
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In medical diagnosis magnetic resonance imaging plays an important role. This work presents a hybrid technique to detect the abnormal parts in the magnetic resonance images of a human being. The proposed technique consists of five stages, namely noise reduction, smoothing, feature extraction, dimensionality reduction or feature reduction and classification. The first stage obtains the MR image with reduced noise using the KSL (Kernel-Sobel-Low pass) filter. In the second stage, smoothing is done by equalizing the histogram. The third stage obtains the characteristics related to the MRI images using discrete wavelet transformation. In the fourth stage, the characteristics of the magnetic resonance images have been reduced using the analysis of components of principles for the most essential characteristics. In the last stage, the classifier based on K-means has been used to classify the subjects as human images of normal or abnormal MRI. The classification accuracy of 98.80% has been obtained by the proposed algorithm.
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