Interactive segmentation algorithm optimized by multi-threshold with application in medical images

Abstract

Interactive image segmentation methods usually ask users to mark much more initial seeds or more than one interaction when they are used for medical image segmentation with fuzzy boundaries.This paper presented an optimized interactive image segmentation algorithm with multi-threshold technology.Based on GorwCut algorithm put forward by Vladimir,the optimized algorithm introduced image gray histogram with more than one threshold values to generate initial seeds template automatically and then used improved cellular automaton iterative algorithm to realize image segmentation.The algorithm simplified the user interactive operations and improved the segmentation accuracy.In applications,the algorithm was used to test on 100 plaque and liver image segmentations respectively,of which the results show that the optimized algorithm is of good performance.