Reconstruction-based 3D/2D image registration

In this paper we present a novel 3D/2D registration method, where first, a 3D image is reconstructed from a few 2D X-ray images and next, the preoperative 3D image is brought into the best possible spatial correspondence with the reconstructed image by optimizing a similarity measure. Because the quality of the reconstructed image is generally low, we introduce a novel asymmetric mutual information similarity measure, which is able to cope with low image quality as well as with different imaging modalities. The novel 3D/2D registration method has been evaluated using standardized evaluation methodology and publicly available 3D CT, 3DRX, and MR and 2D X-ray images of two spine phantoms [1], for which gold standard registrations were known. In terms of robustness, reliability and capture range the proposed method outperformed the gradient-based method [2] and the method based on digitally reconstructed radiographs (DRRs).