Segmentation of Cortical MS Lesions on MRI Using Automated Laminar Profile Shape Analysis

  • Christine L. Tardif
  • D. Louis Collins
  • Simon F. Eskildsen
  • John B. Richardson
  • G. Bruce Pike
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6363)


Cortical multiple sclerosis lesions are difficult to detect in magnetic resonance images due to poor contrast with surrounding grey matter, spatial variation in healthy grey matter and partial volume effects. We propose using an observer-independent laminar profile-based parcellation method to detect cortical lesions. Following cortical surface extraction, profiles are extended from the white matter surface to the grey matter surface. The cortex is parcellated according to profile intensity and shape features using a k-means classifier. The method is applied to a high-resolution quantitative magnetic resonance data set from a fixed post mortem multiple sclerosis brain, and validated using histology.


Multiple Sclerosis Myelin Basic Protein Cortical Lesion Magnetization Transfer Ratio Multiple Sclerosis Pathology 
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  1. 1.
    Bo, L., Vedeler, C.A., Nyland, H.I., Trapp, B.D., Mork, S.J.: Subpial demyelination in the cerebral cortex of multiple sclerosis patients. J. Neuropathol. Exp. Neurol. 62(7), 723–732 (2003)Google Scholar
  2. 2.
    Collins, D.L., Neelin, P., Peters, T.M., Evans, A.C.: Automatic 3D intersubject registration of MR volumetric data in standardized tailarach space. Journal of Computer Assisted Tomography 18(2), 192–205 (1994)CrossRefGoogle Scholar
  3. 3.
    Deoni, S.C., Rutt, B.K., Peters, T.M.: Rapid combined T1 and T2 mapping using gradient recalled acquisition in the steady state. Magn. Reson. Med. 49(3), 515–526 (2003)CrossRefGoogle Scholar
  4. 4.
    Eskildsen, S.F., Ostergaard, L.R.: Active surface approach for extraction of the human cerebral cortex from MRI. In: Int. Conf. Med. Image Comput. Assist. Interv., vol. 9(Pt. 2), pp. 823–830 (2006)Google Scholar
  5. 5.
    Eskildsen, S.F., Ostergaard, L.R., Rodell, A.B., Ostergaard, L., Nielsen, J.E., Isaacs, A.M., Johannsen, P.: Cortical volumes and atrophy rates in FTD-3 CHMP2B mutation carriers and related non-carriers. NeuroImage 45(3), 713–721 (2009)CrossRefGoogle Scholar
  6. 6.
    Geurts, J.J., Pouwels, P.J., Uitdehaag, B.M., Polman, C.H., Barkhof, F., Castelijns, J.A.: Intracortical lesions in multiple sclerosis: improved detection with 3D double inversion-recovery MR imaging. Radiology 236(1), 254–260 (2005)CrossRefGoogle Scholar
  7. 7.
    Kutzelnigg, A., Lucchinetti, C.F., Stadelmann, C., Bruck, W., Rauschka, H., Bergmann, M., Schmidbauer, M., Parisi, J.E., Lassmann, H.: Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain 128(Pt. 11), 2705–2712 (2005)CrossRefGoogle Scholar
  8. 8.
    Schleicher, A., Morosan, P., Amunts, K., Zilles, K.: Quantitative architectural analysis: A new approach to cortical mapping. J. Autism Dev. Disord. (2009)Google Scholar
  9. 9.
    Schmierer, K., Parkes, H.G., So, P.W., An, S.F., Brandner, S., Ordidge, R.J., Yousry, T.A., Miller, D.H.: High field (9.4 Tesla) magnetic resonance imaging of cortical grey matter lesions in multiple sclerosis. Brain 133(Pt. 3), 858–867 (2010)CrossRefGoogle Scholar
  10. 10.
    Sled, J.G., Pike, G.B.: Correction for B(1) and B(0) variations in quantitative T(2) measurements using mri. Magn. Reson. Med. 43(4), 593 (2000)CrossRefGoogle Scholar
  11. 11.
    Sled, J.G., Zijdenbos, A.P., Evans, A.C.: A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans. Med. Imaging 17(1), 87–97 (1998)CrossRefGoogle Scholar
  12. 12.
    Tohka, J., Zijdenbos, A., Evans, A.: Fast and robust parameter estimation for statistical partial volume models in brain MRI. NeuroImage 23(1), 84–97 (2004)CrossRefGoogle Scholar
  13. 13.
    Walters, N.B., Eickhoff, S.B., Schleicher, A., Zilles, K., Amunts, K., Egan, G.F., Watson, J.D.: Observer-independent analysis of high-resolution MR images of the human cerebral cortex: In vivo delineation of cortical areas. Hum. Brain Mapp. 28(1), 1–8 (2007)CrossRefGoogle Scholar
  14. 14.
    Zijdenbos, A.P., Forghani, R., Evans, A.C.: Automatic ‘pipeline’ analysis of 3D MRI data for clinical trials: application to multiple sclerosis. IEEE Transactions on Medical Imaging 21(10), 1280–1291 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Christine L. Tardif
    • 1
  • D. Louis Collins
    • 1
  • Simon F. Eskildsen
    • 2
  • John B. Richardson
    • 3
  • G. Bruce Pike
    • 1
  1. 1.McConnell Brain Imaging CentreMontreal Neurological InstituteCanada
  2. 2.Dept. of Health Science and TechnologyAalborg UniversityDenmark
  3. 3.Dept. of NeuropathologyMontreal Neurological Institute/HospitalCanada

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