Neuroradiology

, Volume 54, Issue 8, pp 787–807 | Cite as

Automated detection of multiple sclerosis lesions in serial brain MRI

  • Xavier Lladó
  • Onur Ganiler
  • Arnau Oliver
  • Robert Martí
  • Jordi Freixenet
  • Laia Valls
  • Joan C. Vilanova
  • Lluís Ramió-Torrentà
  • Àlex Rovira
Continuing Education

Abstract

Introduction

Multiple sclerosis (MS) is a serious disease typically occurring in the brain whose diagnosis and efficacy of treatment monitoring are vital. Magnetic resonance imaging (MRI) is frequently used in serial brain imaging due to the rich and detailed information provided.

Methods

Time-series analysis of images is widely used for MS diagnosis and patient follow-up. However, conventional manual methods are time-consuming, subjective, and error-prone. Thus, the development of automated techniques for the detection and quantification of MS lesions is a major challenge.

Results

This paper presents an up-to-date review of the approaches which deal with the time-series analysis of brain MRI for detecting active MS lesions and quantifying lesion load change. We provide a comprehensive reference source for researchers in which several approaches to change detection and quantification of MS lesions are investigated and classified. We also analyze the results provided by the approaches, discuss open problems, and point out possible future trends.

Conclusion

Lesion detection approaches are required for the detection of static lesions and for diagnostic purposes, while either quantification of detected lesions or change detection algorithms are needed to follow up MS patients. However, there is not yet a single approach that can emerge as a standard for the clinical practice, automatically providing an accurate MS lesion evolution quantification. Future trends will focus on combining the lesion detection in single studies with the analysis of the change detection in serial MRI.

Keywords

Multiple sclerosis Serial analysis MRI Review 

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Xavier Lladó
    • 1
  • Onur Ganiler
    • 1
  • Arnau Oliver
    • 1
  • Robert Martí
    • 1
  • Jordi Freixenet
    • 1
  • Laia Valls
    • 2
  • Joan C. Vilanova
    • 3
  • Lluís Ramió-Torrentà
    • 4
  • Àlex Rovira
    • 5
  1. 1.Computer Vision and Robotics GroupUniversity of GironaGironaSpain
  2. 2.Department of RadiologyDr. Josep Trueta University HospitalGironaSpain
  3. 3.Girona Magnetic Resonance CenterGironaSpain
  4. 4.Multiple Sclerosis and Neuroimmunology UnitDr. Josep Trueta University Hospital, Institut d’Investigació Biomèdica de GironaGironaSpain
  5. 5.Magnetic Resonance Unit, Department of RadiologyVall d’Hebron University HospitalBarcelonaSpain

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