An Automatic Multi-atlas Segmentation of the Prostate in Transrectal Ultrasound Images Using Pairwise Atlas Shape Similarity

  • Saman Nouranian
  • S. Sara Mahdavi
  • Ingrid Spadinger
  • William J. Morris
  • Septimiu E. Salcudean
  • Purang Abolmaesumi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8150)


Delineation of the prostate from transrectal ultrasound images is a necessary step in several computer-assisted clinical interventions, such as low dose rate brachytherapy. Current approaches to user segmentation require user intervention and therefore it is subject to user errors. It is desirable to have a fully automatic segmentation for improved segmentation consistency and speed. In this paper, we propose a multi-atlas fusion framework to automatically segment prostate transrectal ultrasound images. The framework initially registers a dataset of a priori segmented ultrasound images to a target image. Subsequently, it uses the pairwise similarity of registered prostate shapes, which is independent of the image-similarity metric optimized during the registration process, to prune the dataset prior to the fusion and consensus segmentation step. A leave-one-out cross-validation of the proposed framework on a dataset of 50 transrectal ultrasound volumes obtained from patients undergoing brachytherapy treatment shows that the proposed is clinically robust, accurate and reproducible.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Saman Nouranian
    • 1
  • S. Sara Mahdavi
    • 1
  • Ingrid Spadinger
    • 2
  • William J. Morris
    • 2
  • Septimiu E. Salcudean
    • 1
  • Purang Abolmaesumi
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of British ColumbiaVancouverCanada
  2. 2.Vancouver Cancer CenterBritish Columbia Cancer AgencyVancouverCanada

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