Optimizing bone extraction in MR images for 3D/2D gradient based registration of MR and x-ray images

Abstract

A number of intensity and feature based methods have been proposed for 3D to 2D registration. However, for multimodal 3D/2D registration of MR and X-ray images, only hybrid and reconstruction-based methods were shown to be feasible. In this paper we optimize the extraction of features in the form of bone edge gradients, which were proposed for 3D/2D registration of MR and X-ray images. The assumption behind such multimodal registration is that the extracted gradients in 2D X-ray images match well to the corresponding gradients extracted in 3D MR images. However, since MRI and X-rays are fundamentally different modalities, the corresponding bone edge gradients may not appear in the same position and the the above-mentioned assumption may thus not be valid. To test the validity of this assumption, we optimized the extraction of bone edges in 3D MR and also in CT images for the registration to 2D X-ray images. The extracted bone edges were systematically displaced in the direction of their gradients, i.e. in the direction of the normal to the bone surface, and corresponding effects on the accuracy and convergence of 3D/2D registration were evaluated. The evaluation was performed on two different sets of MR, CT and X-ray images of spine phantoms with known gold standard, first consisting of five and the other of eight vertebrae. The results showed that a better registration can be obtained if bone edges in MR images are optimized for each application-specific MR acquisition protocol.