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  • Title: Automatic Brain Portion Segmentation From Magnetic Resonance Images of Head Scans Using Gray Scale Transformation and Morphological Operations.
    Author: Somasundaram K, Ezhilarasan K.
    Journal: J Comput Assist Tomogr; 2015; 39(4):552-8. PubMed ID: 25853776.
    Abstract:
    OBJECTIVE: To develop an automatic skull stripping method for magnetic resonance imaging (MRI) of human head scans. METHODS: The proposed method is based on gray scale transformation and morphological operations. RESULTS: The proposed method has been tested with 20 volumes of normal T1-weighted images taken from Internet Brain Segmentation Repository. Experimental results show that the proposed method gives better results than the popular skull stripping methods Brain Extraction Tool and Brain Surface Extractor. The average value of Jaccard and Dice coefficients are 0.93 and 0.962 respectively. CONCLUSIONS: In this article, we have proposed a novel skull stripping method using intensity transformation and morphological operations. This is a low computational complexity method but gives competitive or better results than that of the popular skull stripping methods Brain Surface Extractor and Brain Extraction Tool.
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