Large deformation registration of contrast-enhanced images with volume-preserving constraint

Kinda Anna Saddi; Christophe Chefd'hotel; Farida Cheriet

doi:10.1117/12.709515

1 March 2007 Large deformation registration of contrast-enhanced images with volume-preserving constraint

Kinda Anna Saddi, Christophe Chefd'hotel, Farida Cheriet

Proceedings Volume 6512, Medical Imaging 2007: Image Processing; 651203 (2007) https://doi.org/10.1117/12.709515
Event: Medical Imaging, 2007, San Diego, CA, United States

Abstract

We propose a registration method for the alignment of contrast-enhanced CT liver images. It consists of a fluid-based registration algorithm designed to incorporate a volume-preserving constraint. More specifically our objective is to recover an accurate non-rigid transformation in a perfusion study in presence of contrast-enhanced structures which preserves the incompressibility of liver tissues. This transformation is obtained by integrating a smooth divergence-free vector field derived from the gradient of a statistical similarity measure. This gradient is regularized with a fast recursive low-pass filter and is projected onto the space of divergence-free vector fields using a multigrid solver. Both 2D and 3D versions of the algorithm have been implemented. Simulations and experiments show that our approach improves the registration capture range, enforces the imcompressibility constraint with a good level of accuracy, and is computationally efficient. On perfusion studies, this method prevents the shrinkage of contrast-enhanced regions typically observed with standard fluid methods.

Citation Download Citation

Kinda Anna Saddi, Christophe Chefd'hotel, and Farida Cheriet "Large deformation registration of contrast-enhanced images with volume-preserving constraint", Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651203 (1 March 2007); https://doi.org/10.1117/12.709515

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