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Efficient 3D Multi-region Prostate MRI Segmentation Using Dual Optimization

  • Wu Qiu
  • Jing Yuan
  • Eranga Ukwatta
  • Yue Sun
  • Martin Rajchl
  • Aaron Fenster
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7917)

Abstract

Efficient and accurate extraction of the prostate, in particular its clinically meaningful sub-regions from 3D MR images, is of great interest in image-guided prostate interventions and diagnosis of prostate cancer. In this work, we propose a novel multi-region segmentation approach to simultaneously locating the boundaries of the prostate and its two major sub-regions: the central gland and the peripheral zone. The proposed method utilizes the prior knowledge of the spatial region consistency and employs a customized prostate appearance model to simultaneously segment multiple clinically meaningful regions. We solve the resulted challenging combinatorial optimization problem by means of convex relaxation, for which we introduce a novel spatially continuous flow-maximization model and demonstrate its duality to the investigated convex relaxed optimization problem with the region consistency constraint. Moreover, the proposed continuous max-flow model naturally leads to a new and efficient continuous max-flow based algorithm, which enjoys great advantages in numerics and can be readily implemented on GPUs. Experiments using 15 T2-weighted 3D prostate MR images, by inter- and intra-operator variability, demonstrate the promising performance of the proposed approach.

Keywords

3D Prostate MRI Zonal Segmentation 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
    • 2
  • Yue Sun
    • 1
    • 2
  • Martin Rajchl
    • 1
    • 2
  • Aaron Fenster
    • 1
    • 2
  1. 1.Robarts Research InstitueWestern UniversityLondonCanada
  2. 2.Department of Biomedical EngineeringWestern UniversityLondonCanada

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