Segmentation of Cortical and Subcortical Multiple Sclerosis Lesions Based on Constrained Partial Volume Modeling

  • Mário João FartariaEmail author
  • Alexis Roche
  • Reto Meuli
  • Cristina Granziera
  • Tobias Kober
  • Meritxell Bach Cuadra
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10435)


We propose a novel method to automatically detect and segment multiple sclerosis lesions, located both in white matter and in the cortex. The algorithm consists of two main steps: (i) a supervised approach that outputs an initial bitmap locating candidates of lesional tissue and (ii) a Bayesian partial volume estimation framework that estimates the lesion concentration in each voxel. By using a “mixel” approach, potential partial volume effects especially affecting small lesions can be modeled, thus yielding improved lesion segmentation. The proposed method is tested on multiple MR image sequences including 3D MP2RAGE, 3D FLAIR, and 3D DIR. Quantitative evaluation is done by comparison with manual segmentations on a cohort of 39 multiple sclerosis early-stage patients.


Cortical lesions Partial volume Multiple sclerosis MRI Lesion segmentation 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Mário João Fartaria
    • 1
    • 2
    • 3
    Email author
  • Alexis Roche
    • 1
    • 2
  • Reto Meuli
    • 2
  • Cristina Granziera
    • 4
    • 5
  • Tobias Kober
    • 1
    • 2
    • 3
  • Meritxell Bach Cuadra
    • 2
    • 3
    • 6
  1. 1.Advanced Clinical Imaging TechnologySiemens Healthcare AGLausanneSwitzerland
  2. 2.Department of RadiologyCHUV and UNILLausanneSwitzerland
  3. 3.Signal Processing Laboratory (LTS 5)EPFLLausanneSwitzerland
  4. 4.Martinos Center for Biomedical Imaging, MGH and HMSChalestownUSA
  5. 5.Department of Clinical NeuroscienceCHUV and UNILLausanneSwitzerland
  6. 6.Center of Biomedical Imaging, CIBMUNILLausanneSwitzerland

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