Isabelle Corouge
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New address
Email: corouge@cs.unc.edu
Address: Department of Computer Science
Campus Box 3175, Sitterson Hall
Chapel Hill, NC 27599-3175
USA

Brief Vitae
Graduated of IFSIC (Higher Institute for Computer Science and Telecommunications), University of Rennes1, in electrical engineering, with a specialization in digital imaging, I have been preparing my PhD thesis since November 1999.

Research Topics
My PhD thesis comes within the scope of 3D cerebral imaging. A great difficulty encountered when processing cerebral data comes from the high variability existing between individuals. Accordingly, modeling the shapes of cerebral structures and their variations among individuals, is of major interest and leads to numerous applications: segmentation, registration, classification, construction of anatomical and functional atlases.

My work first dealt with the statistical modeling of cortical sulci, which are anatomical structures whose shape variations among individuals are complex. Cortex being the privileged locus of functional activity, sulci are relevant objects of interest both from an anatomical point of view as well as from a functional point of view. The model is built from a training population of sulci extracted from MRI volumes, on which is performed a principal components analysis (PCA). (more details)

Two applications have then been considered. On the one hand, we have took part to works about the evaluation of inter-subjects brain registration methods (linear and non linear methods). As a matter of fact, when performed on local landmarks, the statistical analysis provides a similarity measure between registered shapes, and thus provides a comparison criterion between methods.
On the other hand, we have exploited the statistical knowledge acquired by the sulci modeling in the context of anatomical and functional atlases building. More precisely, we have proposed a fusion scheme, local and non-linear, to register inter-subjects functional data (MEG dipoles) toward a single referential linked to the anatomical model of cortical sulci. (more details)

Work in progress aims at extending the statistical modeling of sulci shapes to a complete graph in order to describe not only the morphological features of one sulcus, but also the relationships, in terms of position and orientation, between major sulci.

Selected Publications

I. Corouge, C. Barillot, P. Hellier, P. Toulouse, B. Gibaud. - Non linear local registration of functional data. Medical Image Computing and Computer-Assisted Intervention 2001, MICCAI 2001, W.J. Niessen, M.-A. Viergever (eds), Springer-Verlag, Lecture Notes in Computer Science 2208, pages 948-956, Utrecht, the Netherlands, October 2001. (pdf)