Segmentation of Prostate Using Interactive Finsler Active Contours and Shape Prior

  • Foued Derraz
  • Abdelmalik Taleb-Ahmed
  • Azzeddine Chikh
  • Christina Boydev
  • Laurent Peyrodie
  • Gerard Forzy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7340)

Abstract

We present a new interactive segmentation framework to segment the prostate from MR prostate imagery. We first explicitly address the segmentation problem based on fast globally Finsler Active Contours (FAC) by incorporating both statistical and geometric shape prior knowledge. In doing so, we are able to exploit the more global aspects of segmentation by incorporating user feedback in segmentation process. In addition, once the prostate shape has been segmented, a cost functional is designed to incorporate both the local image statistics as user feedback and the learned shape prior. We provide experimental results, which include several challenging clinical data sets, to highlight the algorithm’s capability of robustly handling supine/prone prostate segmentation task.

Keywords

Finsler Active contours characteristic function shape prior user interaction 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Foued Derraz
    • 1
    • 3
  • Abdelmalik Taleb-Ahmed
    • 3
  • Azzeddine Chikh
    • 4
  • Christina Boydev
    • 3
  • Laurent Peyrodie
    • 2
  • Gerard Forzy
    • 1
  1. 1.Faculté Libre de MédicineInstitut Catholique de LilleFrance
  2. 2.HEI, LAGIS UMR CNRS 3304LilleFrance
  3. 3.LAMIH UMR CNRS 8201ValenciennesFrance
  4. 4.Biomedical Engineering Laboratory, Technology CollegeAbou Bekr Belkaid UniversityAlgeria

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