A novel method for segmentation of the Hippocampus based on watershed algorithm

One of the main area under medical research is the analysis of brain image. A lot of researches are going on for segmenting the brain images automatically. Hippocampus is an important component of brain which plays an important role in the normal behaviour of the human beings. It is a new region of research now. It takes many hours for a specialist in this area to segment the Hippocampus manually. There are many techniques available for the segmentation process. Watershed algorithm for segmentation is an easiest and fastest method and a modified approach for segmenting the Hippocampus region of the brain has been presented in this paper. Initially enhancement is done for better processing and result. Then an enhancement is done based on the watershed algorithm using the bottom hat and the top hat of the image. This enhanced image is converted into a binary image based on the threshold value found by the trial and error method. The edges of this image are detected and then the disconnected components are extracted using the labelling concept. The two components consisting of the right and the left hippocampus regions have been successfully extracted.