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Entropy-Based Automatic Segmentation of Bones in Digital X-ray Images

  • Oishila Bandyopadhyay
  • Bhabatosh Chanda
  • Bhargab B. Bhattacharya
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6744)

Abstract

Bone image segmentation is an integral component of orthopedic X-ray image analysis that aims at extracting the bone structure from the muscles and tissues. Automatic segmentation of the bone part in a digital X-ray image is a challenging problem because of its low contrast with the surrounding flesh, which itself needs to be discriminated against the background. The presence of noise and spurious edges further complicates the segmentation. In this paper, we propose an efficient entropy-based segmentation technique that integrates several simple steps, which are fully automated. Experiments on several X-ray images reveal encouraging results as evident from a segmentation entropy quantitative assessment (SEQA) metric [Hao, et al. 2009].

Keywords

Entropy Digital X-ray LOCO Medical imaging Segmentation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Oishila Bandyopadhyay
    • 1
  • Bhabatosh Chanda
    • 2
  • Bhargab B. Bhattacharya
    • 2
  1. 1.Department of CSECamellia Institute of TechnologyKolkataIndia
  2. 2.Center for Soft Computing ResearchIndian Statistical InstituteKolkataIndia

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