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Fast Globally Optimal Segmentation of 3D Prostate MRI with Axial Symmetry Prior

  • Wu Qiu
  • Jing Yuan
  • Eranga Ukwatta
  • Yue Sun
  • Martin Rajchl
  • Aaron Fenster
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8150)

Abstract

We propose a novel global optimization approach to segmenting a given 3D prostate T2w magnetic resonance (MR) image, which enforces the inherent axial symmetry of the prostate shape and simultaneously performs a sequence of 2D axial slice-wise segmentations with a global 3D coherence prior. We show that the proposed challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. With this regard, we introduce a novel coupled continuous max-flow model, which is dual to the studied convex relaxed optimization formulation and leads to an efficient multiplier augmented algorithm based on the modern convex optimization theory. Moreover, the new continuous max-flow based algorithm was implemented on GPUs to achieve a substantial improvement in computation. Experimental results using public and in-house datasets demonstrate great advantages of the proposed method in terms of both accuracy and efficiency.

Keywords

Prostate MRI segmentation axial symmetry convex optimization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Wu Qiu
    • 1
  • Jing Yuan
    • 1
  • Eranga Ukwatta
    • 1
  • Yue Sun
    • 1
  • Martin Rajchl
    • 1
  • Aaron Fenster
    • 1
  1. 1.Robarts Research InstituteUniversity of Western OntarioCanada

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