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Statistical shape and texture model of quadrature phase information for prostate segmentation

  • Original Article
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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Prostate volume estimation from segmentation of transrectal ultrasound (TRUS) images aids in diagnosis and treatment of prostate hypertrophy and cancer. Computer-aided accurate and computationally efficient prostate segmentation in TRUS images is a challenging task, owing to low signal-to-noise ratio, speckle noise, calcifications, and heterogeneous intensity distribution in the prostate region.

Method

A multi-resolution framework using texture features in a parametric deformable statistical model of shape and appearance was developed to segment the prostate. Local phase information of log-Gabor quadrature filter extracted texture of the prostate region in TRUS images. Large bandwidth of log-Gabor filter ensures easy estimation of local orientations, and zero response for a constant signal provides invariance to gray level shift. This aids in enhanced representation of the underlying texture information of the prostate unaffected by speckle noise and imaging artifacts. The parametric model of the propagating contour is derived from principal component analysis of prior shape and texture information of the prostate from the training data. The parameters were modified using prior knowledge of the optimization space to achieve segmentation.

Results

The proposed method achieves a mean Dice similarity coefficient value of 0.95 ± 0.02 and mean absolute distance of 1.26 ± 0.51 millimeter when validated with 24 TRUS images of 6 data sets in a leave-one-patient-out validation framework.

Conclusions

The proposed method for prostate TRUS image segmentation is computationally efficient and provides accurate prostate segmentations in the presence of intensity heterogeneities and imaging artifacts.

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Authors and Affiliations

  1. Computer Vision and Robotics Group, University of Girona, Campus Montilivi, Edifici P-IV, 17071, Girona, Spain

    Soumya Ghose, Arnau Oliver, Robert Martí, Xavier Lladó, Jordi Freixenet & Jhimli Mitra

  2. Clinica Girona, Calle Joan Maragall 26, 17002, Girona, Spain

    Joan C. Vilanova

  3. Division of Urology, University Hospital Dr. Josep Trueta, Av. França, 17007, Girona, Spain

    Josep Comet-Batlle

  4. Laboratoire Le2I, UMR CNRS 5158, Université de Bourgogne, 12 Rue de la Fonderie, 71200, Le Creusot, Bourgogne, France

    Soumya Ghose, Jhimli Mitra & Fabrice Meriaudeau

Authors
  1. Soumya Ghose
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  2. Arnau Oliver
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  3. Robert Martí
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  4. Xavier Lladó
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  6. Jhimli Mitra
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  7. Joan C. Vilanova
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  9. Fabrice Meriaudeau
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Correspondence to Soumya Ghose.

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Ghose, S., Oliver, A., Martí, R. et al. Statistical shape and texture model of quadrature phase information for prostate segmentation. Int J CARS 7, 43–55 (2012). https://doi.org/10.1007/s11548-011-0616-y

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  • DOI: https://doi.org/10.1007/s11548-011-0616-y

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