Date-driven Based Image Enhancement for Segmenting of MS Lesions in T2-w and Flair MRI

  • Ziming Zeng
  • Zhonghua Han
  • Yitian Zhao
  • Reyer Zwiggelaar
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)

Abstract

This paper proposed a data-driven based image enhancement scheme to segment Multiple Sclerosis (MS) lesions. It utilizes a class-adaptive Gaussian Markov random field modelling (HMRF) and mutual information to automatic enhance the MS lesions. Then an alpha matting technique is used to refine the segmentation results. The advantages of the approach lies in its date-driven processing. It can automatically enhance the density of MS lesions, which is guided by calculating the mutual information value of the segmentation results in the successive steps. In addition, the partial volume effects are considered and the regions of interests are segmented in a sub-pixel precision. The experiments on real MR images show the proposed segmentation method can effectively segment MS lesions.

Keywords

Date-driven Enhancement MS lesions Segmentation Mutual information 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Ziming Zeng
    • 1
    • 2
  • Zhonghua Han
    • 1
  • Yitian Zhao
    • 2
  • Reyer Zwiggelaar
    • 2
  1. 1.Information and Control Engineering FacultyShenyang Jianzhu UniversityLiaoningChina
  2. 2.Department of Computer ScienceAberystwyth UniversityAberystwythUK

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