Computer Science ›› 2017, Vol. 44 ›› Issue (Z6): 198-201.doi: 10.11896/j.issn.1002-137X.2017.6A.045

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Image Segmentation Algorithm Based on Clustering and Improved Double Level Set

ZHANG Hui, ZHU Jia-ming and TANG Wen-jie   

  • Online:2017-12-01 Published:2018-12-01

Abstract: Usually,medical image accompanied by noise with a multi-objective problem,can not be separated completely by traditional level set in the image with multiple targets.This paper proposed a model based on inhibiting type of fuzzy clustering algorithm and modified double level set.First of all,the clustering algorithm is used for pre segmentation of medical image noise reduction,which can determine whether a cluster achieves satisfied effect through standardized rule of normalized mutual information (NMI),thus improving clustering algorithm. The improved double level set with pu-nishment item is given a second segmentation finally.The experimental results show that the method can reduce the noise of the image and the sensitivity of the algorithm,without reinitialize level set,reducing the amount of calculation and the number of iteration greatly.The model can separate medical image including noise and multiple objects completely,obtaining the expected effect of segmentation.

Key words: Medical image segmentation,Clustering,NMI,Double level set

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