Abstract
The task of manual brain segmentation from magnetic resonance imaging (MRI) is generally time-consuming and difficult. In a previous paper [1], we described a method for segmenting MR which is based on EM algorithm and a deformable level-set model. However, this method was not fully automatic. In this paper, we present an automated approach guided by digital anatomical atlas, which is an additional source of prior information. Our fully automatic method segments white matter, grey matter and cerebrospinal-fluid. The paper describes the main stages of the method, and presents preliminary results which are very encouraging for clinical practice.
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Bourouis, S., Hamrouni, K., Betrouni, N. (2008). Automatic MRI Brain Segmentation with Combined Atlas-Based Classification and Level-Set Approach. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_76
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DOI: https://doi.org/10.1007/978-3-540-69812-8_76
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