An Approach to CT Stomach Image Segmentation Using Modified Level Set Method

Internal organs of a human body have very complex structure owing to their anatomic organization. Several image segmentation techniques fail to segment the various organs from medical images due to simple biases. Here, a modified version of the level set method is employed to segment the stomach from CT images. Level set is a model based segmentation method that incorporates a numerical scheme. For the sake of stability of the evolving zero'th level set contour, instead of periodic reinitialization of the signed distance function, a distance regularization term is included. This term is added to the energy optimization function which when solved with gradient flow algorithms, generates a solution with minimum energy and maximum stability. Evolution of the contour is controlled by the edge indicator function. The results show that the algorithm is able to detect inner boundaries in the considered CT stomach images. It appears that it is also possible to extract outer boundaries as well. The results of this approach are reported in this paper.