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Annual Conference on Medical Image Understanding and Analysis

MIUA 2017: Medical Image Understanding and Analysis pp 309–319Cite as

3D Texton Based Prostate Cancer Detection Using Multiparametric Magnetic Resonance Imaging

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 723))

Abstract

Multiparametric magnetic resonance imaging (mp-MRI) has shown its potential in prostate cancer detection. In this study, we investigate the application of 3D texton based prostate cancer detection using T2-weighted (T2W) MRI, dynamic contrast-enhanced (DCE) MRI and apparent diffusion coefficient (ADC) maps. For the T2W and ADC modalities, the traditional texton based approach is adopted, i.e., for each voxel, a texton histogram is extracted as the feature to perform the classification. For the DCE data, we present a new method, where the textons are extracted from each series and for each voxel, the corresponding textons across all series are used as features. A random forest classifier is applied for classifying all voxels into benign or malignant. The evaluation is conducted by performing a receiver operating characteristics (ROC) analysis and computing the area under the curve (AUC). The experiments on the Initiative for Collaborative Computer Vision Benchmarking (I2CVB) database demonstrate that the texton based approach using mp-MRI data obtains excellent performance in prostate cancer detection and produces \(88.3\%\) accuracy, whereas the accuracy produced by an intensity based approach is \(79.8\%\).

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Notes

  1. 1.

    https://github.com/I2Cvb/mp-mri-prostate.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Aberystwyth University, Aberystwyth, SY23 3DB, UK

    Liping Wang & Reyer Zwiggelaar

Authors
  1. Liping Wang
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  2. Reyer Zwiggelaar
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Correspondence to Liping Wang .

Editor information

Editors and Affiliations

  1. Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom

    María Valdés Hernández

  2. University of León, León, Spain

    Víctor González-Castro

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Wang, L., Zwiggelaar, R. (2017). 3D Texton Based Prostate Cancer Detection Using Multiparametric Magnetic Resonance Imaging. In: Valdés Hernández, M., González-Castro, V. (eds) Medical Image Understanding and Analysis. MIUA 2017. Communications in Computer and Information Science, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-319-60964-5_27

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  • DOI: https://doi.org/10.1007/978-3-319-60964-5_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60963-8

  • Online ISBN: 978-3-319-60964-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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