Abstract
In this work, subcortical regions of autism spectrum disorder are analysed using fuzzy Gaussian distribution model-based distance regularised multi-phase level set method in autistic MR brain images. The fuzzy Gaussian distribution model is used as the intensity discriminator. The segmented images are validated with the ground truth using geometrical measure area. The results show that the fuzzy Gaussian distribution model-based multi-phase level set method is able to extract the subcortical tissue boundaries. The subcortical regions segmented using this method gives high correlation with ground truth. The corpus callosum area gives very high (R = 0.94) correlation. The brain stem and cerebellum present high correlations of 0.89 and 0.84, respectively. Also, it is found the segmented autistic subcortical regions have reduced area and are statistically significant (p < 0.0001). The ratio metric analysis proves the relation in reduction of the area in subcortical regions with total brain area.
Published Version
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