Automatic brain MRI image segmentation using FCM and LSM
Pratibha Singh, H.S. Bhadauria, Annapurna Singh · 2014
The significant objective of this paper is to produce a method that is able to delineate the object of interest or tumor region easily from the available brain MRI images. This is attained by the unification of the fuzzy c-means clustering and level set method. The method proposed performs the segmentation by smoothly exploiting the spatial function during FCM clustering. Since, we are utilizing the FCM which could prove the automaticity of the method by dividing the original image into clusters and then using one cluster for automatic initialization. This in turn helps in making the whole processing less tedious with reducing the time as well. Thereby, if considered it could be competent tool in future. Secondly, to find the contour of tumor region in the original image the proposed method uses the level set method which comes in handy in situations where the topologies of the images changes frequently by merging or splitting in two. Also, the proposed methodology makes use of variational level method in place of generic level set method which in turn eliminates one more flaw of re- initializing the contour during segmentation. When we are using the segmentation methods which are manual then it can lead to a situation where different medical experts generate different results which can also overcome by using the proposed approach.