Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 256-258,277.

• Pattem Recognition & Image Processing • Previous Articles     Next Articles

Double Level Set Algorithm Based on NL-Means Denosing Method for Brain MR Images Segmentation

TANG Wen-jie, ZHU Jia-ming XU Li   

  1. School of Information Engineering,Yangzhou University,Yangzhou,Jiangsu 225127,China
  • Online:2019-02-26 Published:2019-02-26

Abstract: This paper proposed a novel double level set algorithm based on NL-Means denosing method for brain MR image segmentation,which has a large amount of noise and complicated background,and cannot be separated completely by traditional level set.First of all,this algorithm gets the denoised image by analyzing the image with NL-Means denosing method.Then,the algorithm identifies denoised image by segmenting the analyzed results in terms of improved double level set model.In order to deal with the effect of intensity inhomogeneities on the medical image,the algorithm introduces a bias fitting term into the improved double level set model and optimizes the denosing method result.The experimental result shows that the algorithm can reduce the problems of intensity inhomogeneities and noise,can separate brain MR image including intensity inhomogeneities and noise completely,and can obtain the expected effect of segmentation.

Key words: Medical image, NL-Means, Double level set, Bias correction

CLC Number: 

  • TP391
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