Title: Segmentation of mice cerebral structures: application in Trisomy 21

Authors: Ahmad Almhdie-Imjabber; José Manuel Ferrer-Villena; Rachid Harba; Roger Lédée; Christophe Léger; Patricia Lopes-Pereira; Sandra Même

Addresses: PRISME Laboratory, University of Orleans, 12, Rue de Blois, 45067 Orleans, France; EE Department, Faculty of Engineering, University of Sebha, P.O. Box: 68, Brack Ashati, Libya. ' PRISME Laboratory, University of Orleans, 12, Rue de Blois, 45067 Orleans, France. ' PRISME Laboratory, University of Orleans, 12, Rue de Blois, 45067 Orleans, France. ' PRISME Laboratory, University of Orleans, 12, Rue de Blois, 45067 Orleans, France. ' PRISME Laboratory, University of Orleans, 12, Rue de Blois, 45067 Orleans, France. ' IEM Laboratory, CNRS, 3B Rue de la Férollerie, 45071 Orleans, France. ' CBM Laboratory, CNRS, Rue Charles Sadron, 45071 Orleans, France

Abstract: In this paper, a semi automatic method is proposed for the segmentation of mice cerebral structures (brain, cerebellum and hippocampus) in MR images. First, a Chan-Vese method is applied on the axial images to segment the brain volume. The method takes into account the special shape of the brain mice. Second, variational atlases are constructed by manual segmentation of various MRI brain images of reference and Trisomy 21 mice. These atlases are then registered on true data to assist the Chan-Vese segmentation of the cerebellum and the hippocampus. This semi automatic method makes that human intervention is limited and the tedious manual handling is greatly reduced. Results have shown that the brain volumes estimated by the method are identical to expert manually estimated volumes. The new method was used in the analysis of the cerebral malformations linked to Trisomy 21: no significant difference of the cerebral structures between Trisomy 21 mice and the control ones was found.

Keywords: Chan-Vese segmentation; active contour; Atlas registration; MRI cerebral images; Trisomy 21; mice cerebral structures; brain; cerebellum; hippocampus; magnetic resonance imaging; semi-automatic segmentation; cerebral malformation.

DOI: 10.1504/IJICA.2012.050057

International Journal of Innovative Computing and Applications, 2012 Vol.4 No.3/4, pp.214 - 222

Received: 02 May 2011
Accepted: 22 Dec 2011
Published online: 22 Sep 2014 *

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