Segmentation from Images Using Adaptive Threshold

Liver segmentation is an important prerequisite for planning of surgical interventions like liver tumor resections. In this paper we propose a method for automated liver segmentation from images that is invariant in provisions of size, shape and intensity values. The system consists of three stages. In the first stage of the computerized system, Preprocessing of an image is done to reduce the noise and to enhance the image for further processing. In the second stage, liver region is segmented from the liver image. The liver is segmented from images using adaptive threshold finding and morphological processing. In the third stage, post processing enhancement is done on the segmented liver region to increase the contrast of liver region. Experimental results show that our propose technique segments the liver region with accuracy.