Abstract
The extent and the location of the multiple sclerosis plaques in the MR image of the brain are important criteria for the prognosis and diagnosis. The segmentation of lesions by manual delineation is extremely difficult and a tedious task due to observer variability, in addition to anatomical variability between subjects. In multiple sclerosis, lesions segmentation has become a crucial criterion, for this reason, automated lesion segmentation and evaluation are not only desirable with regard to time and cost-effectiveness but also constitute a necessary condition to minimize user bias. In this contribution, we propose an automatic method for lesions delineation based on MR images. In this approach, 3D FLAIR-weighted, with 3 Tesla magnetic field, is used to image lesions in the white matter while segmenting the brain tissue. Our approach allows the automatic identification of these lesions. Our results are validated quantitatively with the public database “BrainWeb”, “ISBI2015”, MICCAI2008, and “MICCAI2016.”
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Dachraoui, C., Mouelhi, A., Drissi, C., Labidi, S. (2022). Automated Diagnosis of Multiple Sclerosis Lesions in Brain MRI Using 3D-FLAIR Acquisition. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Proceedings of Sixth International Congress on Information and Communication Technology. Lecture Notes in Networks and Systems, vol 217. Springer, Singapore. https://doi.org/10.1007/978-981-16-2102-4_1
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DOI: https://doi.org/10.1007/978-981-16-2102-4_1
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