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A toolbox for multiple sclerosis lesion segmentation

  • Diagnostic Neuroradiology
  • Published:
Neuroradiology Aims and scope Submit manuscript

Abstract

Introduction

Lesion segmentation plays an important role in the diagnosis and follow-up of multiple sclerosis (MS). This task is very time-consuming and subject to intra- and inter-rater variability. In this paper, we present a new tool for automated MS lesion segmentation using T1w and fluid-attenuated inversion recovery (FLAIR) images.

Methods

Our approach is based on two main steps, initial brain tissue segmentation according to the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) performed in T1w images, followed by a second step where the lesions are segmented as outliers to the normal apparent GM brain tissue on the FLAIR image.

Results

The tool has been validated using data from more than 100 MS patients acquired with different scanners and at different magnetic field strengths. Quantitative evaluation provided a better performance in terms of precision while maintaining similar results on sensitivity and Dice similarity measures compared with those of other approaches.

Conclusion

Our tool is implemented as a publicly available SPM8/12 extension that can be used by both the medical and research communities.

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Notes

  1. http://www.ia.unc.edu/MSseg/results_table.php

  2. http://www.fil.ion.ucl.ac.uk/spm

  3. http://atc.udg.edu/salem/slsToolbox/index.html

  4. http://www.fmrib.ox.ac.uk/fsl/fslwiki/BET

  5. http://www.itk.org

  6. http://www.nitrc.org/projects/un_correct/

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Acknowledgments

E. Roura holds a BRUdG2013 grant. S. Valverde holds a FI-DGR2013 grant from the Generalitat de Catalunya. This work has been partially supported by “La Fundació la Marató de TV3” and by Retos de Investigación TIN2014-55710-R.

Ethical standards and patient consent

We declare that all human studies have been approved by the appropriate Ethics Committee and have therefore been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. We declare that patient consent was waived due to the retrospective nature of this study.

Conflict of interest

We declare that we have no conflict of interest.

Author information

Authors and Affiliations

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

    Eloy Roura, Arnau Oliver, Sergi Valverde & Xavier Lladó

  2. Magnetic Resonance Unit, Dept. of Radiology, Vall d’Hebron University Hospital, Barcelona, Spain

    Mariano Cabezas, Deborah Pareto & Àlex Rovira

  3. Girona Magnetic Resonance Center, Girona, Spain

    Joan C. Vilanova

  4. Multiple Sclerosis and Neuroimmunology Unit, Dr. Josep Trueta University Hospital, Institut d’Investigació Biomèdica de Girona, Girona, Spain

    Lluís Ramió-Torrentà

Authors
  1. Eloy Roura
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  2. Arnau Oliver
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Correspondence to Eloy Roura.

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Roura, E., Oliver, A., Cabezas, M. et al. A toolbox for multiple sclerosis lesion segmentation. Neuroradiology 57, 1031–1043 (2015). https://doi.org/10.1007/s00234-015-1552-2

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  • DOI: https://doi.org/10.1007/s00234-015-1552-2

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