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The Classification of Meningioma Subtypes Based on the Color Segmentation and Shape Features

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

Abstract

This paper proposed an automatic method for the classification of meningioma subtypes based on the unsupervised color segmentation method and feature selection scheme. Firstly, a color segmentation method is utilized to segment the cell nuclei. Then the set of shape feature vectors which are calculated from the segmentation results are constructed. Finally, a k-nearest neighbour classifier (kNN) is used to classify the meningioma subtypes. Experiment shows that the classification accuracy of 85 % is achieved by using a leave-one-out cross validation approach on 80 meningioma images.

Keywords

Meningioma Segmentation Classification Color Shape features 

References

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    Qureshi H, Sertel O, Rajpoot N, Wilson R, Gurcan M (2008) Adaptive discriminant wavelet packet transform and local binary patterns for meningioma subtype classification. In: Proceedings 11th medical image computing and computer-assisted intervention. Lecture notes in computer science, vol 5242, pp 196–204Google Scholar
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    Qureshi H, Rajpoot N, Nattkemper T, Hans V (2009) A robust adaptive wavelet- based method for classification of meningioma histology images. In: Proceedings of MICCAI workshop on optical tissue image analysis in microscopy, histopathology and endoscopyGoogle Scholar
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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Ziming Zeng
    • 1
    • 2
  • Zeng Tong
    • 3
  • Zhonghua Han
    • 1
    • 4
  • Yinlong Zhang
    • 4
  • Reyer Zwiggelaar
    • 2
  1. 1.Information and Control Engineering FacultyShenyang Jianzhu UniversityLiaoningChina
  2. 2.Department of Computer ScienceAberystwyth UniversityAberystwythUK
  3. 3.School of ManagementShenyang Jianzhu UniversityShenyangChina
  4. 4.Shenyang Institute of AutomationChinese Academy of ScienceShenyangChina

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