Liver CT image segmentation based on prior shape CV model
Yuqian Zhao · Journal of Optoelectronics·laser · 2010
CV model can not segment correctly under the condition that some essential information is missed partly or some parts of the objects are occluded.To solve this problem,a new model based on prior shape focusing on detecting occluded objects is proposed.The new model firstly constructs prior shape which is obtained by mathematical morphology combining with other algorithms,then integrates the prior shape into CV model functional through a novel signed distance function,in which the signed function is constructed by fast implemented boundary searching algorithm and region labeling.The proposed method is applied to segment liver from CT images,with noises around boundary or part of liver being occluded.Compared with the results of CV model,the experimental results show that the new model can detect occluded liver from CT images successfully.