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Computer-aided analysis of prostate multiparametric MR images: an unsupervised fusion-based approach

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

Abstract

Objective

The aim of this study is to provide an automatic framework for computer-aided analysis of multiparametric magnetic resonance (mp-MR) images of prostate.

Method

We introduce a novel method for the unsupervised analysis of the images. An evidential C-means classifier was adapted for use with a segmentation scheme to address multisource data and to manage conflicts and redundancy.

Results

Experiments were conducted using data from 15 patients. The evaluation protocol consisted in evaluating the method abilities to classify prostate tissues, showing the same behaviour on the mp-MR images, into homogeneous classes. As the actual diagnosis was available, thanks to the correlation with histopathological findings, the assessment focused on the ability to segment cancer foci. The method exhibited global sensitivity and specificity of 70 and 88 %, respectively.

Conclusion

The preliminary results obtained by these initial experiments showed that the method can be applied in clinical routine practice to help making decision especially for practitioners with limited experience in prostate MRI analysis.

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Conflict of interest

Nacim Betrouni, Nasr Makni, Said Lakroum, Philippe Puech, Arnauld Villers and Serge Mordon declare that they have no conflict of interest.

Informed consent Informed consent was obtained from all patients for being included in the study.

Author information

Authors and Affiliations

  1. INSERM, U703, 152, rue du Docteur Yersin, 59120, Loos, CHRU de Lille, France

    N. Betrouni, N. Makni, S. Lakroum, S. Mordon, A. Villers & P. Puech

  2. Université de Lille II, Lille, France

    N. Betrouni, S. Mordon, A. Villers & P. Puech

  3. Radiology Department, Hôpital Claude Huriez, Lille University Hospital, Lille, France

    P. Puech

  4. Urology Department, Hôpital Claude Huriez, Lille University Hospital, Lille, France

    A. Villers

Authors
  1. N. Betrouni
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  2. N. Makni
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  3. S. Lakroum
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  4. S. Mordon
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  5. A. Villers
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  6. P. Puech
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Correspondence to N. Betrouni.

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Betrouni, N., Makni, N., Lakroum, S. et al. Computer-aided analysis of prostate multiparametric MR images: an unsupervised fusion-based approach. Int J CARS 10, 1515–1526 (2015). https://doi.org/10.1007/s11548-015-1151-z

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  • DOI: https://doi.org/10.1007/s11548-015-1151-z

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