Abstract
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.
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Keywords
- Multiple Sclerosis
- Myelin Basic Protein
- Cortical Lesion
- Magnetization Transfer Ratio
- Multiple Sclerosis Pathology
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Tardif, C.L., Collins, D.L., Eskildsen, S.F., Richardson, J.B., Pike, G.B. (2010). Segmentation of Cortical MS Lesions on MRI Using Automated Laminar Profile Shape Analysis. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010. MICCAI 2010. Lecture Notes in Computer Science, vol 6363. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15711-0_23
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DOI: https://doi.org/10.1007/978-3-642-15711-0_23
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