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Neuroradiology

, Volume 57, Issue 10, pp 1031–1043 | Cite as

A toolbox for multiple sclerosis lesion segmentation

  • Eloy RouraEmail author
  • Arnau Oliver
  • Mariano Cabezas
  • Sergi Valverde
  • Deborah Pareto
  • Joan C. Vilanova
  • Lluís Ramió-Torrentà
  • Àlex Rovira
  • Xavier Lladó
Diagnostic Neuroradiology

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.

Keywords

Multiple sclerosis Magnetic resonance images Lesion detection Lesion segmentation Automated tool 

Notes

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Eloy Roura
    • 1
    Email author
  • Arnau Oliver
    • 1
  • Mariano Cabezas
    • 2
  • Sergi Valverde
    • 1
  • Deborah Pareto
    • 2
  • Joan C. Vilanova
    • 3
  • Lluís Ramió-Torrentà
    • 4
  • Àlex Rovira
    • 2
  • Xavier Lladó
    • 1
  1. 1.Computer Vision and Robotics GroupUniversity of GironaGironaSpain
  2. 2.Magnetic Resonance Unit, Dept. of RadiologyVall d’Hebron University HospitalBarcelonaSpain
  3. 3.Girona Magnetic Resonance CenterGironaSpain
  4. 4.Multiple Sclerosis and Neuroimmunology UnitDr. Josep Trueta University Hospital, Institut d’Investigació Biomèdica de GironaGironaSpain

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