Surface modeling of the corpus callosum from MRI scans

Authors:
Ahmed Farag;Shireen Elhabian;Mostafa Abdelrahman;James Graham;Aly Farag;Dongqing Chen;Manuel F. Casanova
Affiliations:
Department of Electrical and Computer Engineering, University of Louisville;Department of Electrical and Computer Engineering, University of Louisville;Department of Electrical and Computer Engineering, University of Louisville;Department of Electrical and Computer Engineering, University of Louisville;Department of Electrical and Computer Engineering, University of Louisville;Department of Electrical and Computer Engineering, University of Louisville;Department of Psychiatry, University of Louisville
Venue:
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
Year:
2010

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Abstract

In this paper, the Bezier curve and surface are used to model the shape of the Corpus Callosum (CC) region from T1-weighted clinical MRI scans. We drive a closed form solution for the Bezier coefficients in 2D and 3D Euclidean spaces. The coefficients of the models are used for reconstruction of the CC contours and surfaces with varying degrees of accuracy, and constitute basis for discrimination between populations, and ways to enhance elastic registration of the CC. The discrimination ability of the Bezier curves and surfaces are evaluated against the Fourier Descriptors (FD) and Spherical Harmonics (SH) approaches.