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An Integrated Algorithm for MRI Brain Images Segmentation

  • Yinghua Lu
  • Jianzhong Wang
  • Jun Kong
  • Baoxue Zhang
  • Jingdan Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4241)

Abstract

This paper presents an integrated algorithm for MRI (Magnetic Resonance Imaging) brain tissues segmentation. The method is composed of four stages. Noise in the MRI images is first reduced by a versatile wavelet-based filter. Then, the watershed algorithm is applied to brain tissues as an initial segmenting method. Because the result of classical watershed algorithm on grey-scale textured images such as tissue images is over-segmentation. The third stage is a merging process for the over-segmentation regions using fuzzy clustering algorithm (Fuzzy C-Means). But there are still some regions which are not divided completely due to the low contrast in them, particularly in the transitional regions of gray matter and white matter, or cerebrospinal fluid and gray matter. We exploited a method base on Minimum Covariance Determinant (MCD) estimator to detect the regions needed segmentation again, and then partition them by a supervised k-Nearest Neighbor (kNN) classifier. This integrated approach yields a robust and precise segmentation. The efficacy of the proposed algorithm is validated using extensive experiments.

Keywords

Gray Matter Integrate Algorithm Transitional Region Fuzzy Cluster Algorithm Watershed Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yinghua Lu
    • 1
    • 2
  • Jianzhong Wang
    • 2
    • 3
  • Jun Kong
    • 2
    • 3
  • Baoxue Zhang
    • 3
  • Jingdan Zhang
    • 2
  1. 1.Computer SchoolJilin UniversityChangchun, Jilin ProvinceChina
  2. 2.Computer SchoolNortheast Normal UniversityChangchun, Jilin ProvinceChina
  3. 3.Key Laboratory for Applied Statistics of MOEChina

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