Automatic MRI Brain Segmentation with Combined Atlas-Based Classification and Level-Set Approach

Authors:
Sami Bourouis;Kamel Hamrouni;Nacim Betrouni
Affiliations:
National Engineering School of Tunis System and Signal Processing Laboratory, University Tunis El Manar, Tunis, Tunisia 1002;National Engineering School of Tunis System and Signal Processing Laboratory, University Tunis El Manar, Tunis, Tunisia 1002;Inserm, U703, ITM Pavillon Vancostenobel, University Hospital of Lille, France
Venue:
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Year:
2008

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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.