Abstract
We propose to segment Multiple Sclerosis (MS) lesions overtime in multidimensional Magnetic Resonance (MR) sequences. We use a robust algorithm that allows the segmentation of the abnormalities using the whole time series simultaneously and we propose an original rejection scheme for outliers. We validate our method using the BrainWeb simulator. To conclude, promising preliminary results on longitudinal multi-sequences of clinical data are shown.
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Keywords
- Multiple Sclerosis
- Maximum Likelihood Estimator
- Gaussian Mixture Model
- Mahalanobis Distance
- Multiple Sclerosis Lesion
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Aït-Ali, L.S., Prima, S., Hellier, P., Carsin, B., Edan, G., Barillot, C. (2005). STREM: A Robust Multidimensional Parametric Method to Segment MS Lesions in MRI. In: Duncan, J.S., Gerig, G. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005. MICCAI 2005. Lecture Notes in Computer Science, vol 3749. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11566465_51
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DOI: https://doi.org/10.1007/11566465_51
Publisher Name: Springer, Berlin, Heidelberg
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