White Matter Hyperintensity segmentation using multiple stage FCM
Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India
| Hi-index | 0.00 |
This paper deals with an automatic and relatively efficient method for estimating intracranial volume from MR brain images. The proposed method consists of mainly three steps, namely skull removal, image segmentation and volume calculation. The present method uses morphological operations followed by 3Dconnected component labeling and image subtraction for extracting the brain mask from the original brain slices. The skull stripped images are then segmented into the three tissues namely Gray Matter, White Matter and Cerebrospinal fluid using an efficient clustering technique namely, Weighted k-means clustering algorithm followed by Expectation Maximization algorithm. Finally the volume of the segmented tissues is calculated using Cavalier's estimator of morphometric volume method and some sample results are presented. The proposed method gives reliable results for making quantitative analysis and diagnosis of tissues from Magnetic Resonance brain image slices.