This paper presents a novel method for computing simulated x-ray images, or DRRs (digitally reconstructed radiographs), of tetrahedral meshes with higher-order attenuation functions. DRRs are commonly used in computer assisted surgery (CAS), with the attenuation function consisting of a voxelized CT study, which is viewed from different directions. Our application of DRRs is in intra-operative “2D-3D” registration, i.e., finding the pose of the CT dataset given a small number of patient radiographs. We register 2D patient images with a statistical tetrahedral model, which encodes the CT intensity numbers as Bernstein polynomials, and includes knowledge about typical shape variation modes. The unstructured grid is more suitable for applying deformations than a rectilinear grid, and the higher-order polynomials provide a better approximation of the actual density than constant or linear models. The intra-operative environment demands a fast method for creating the DRRs, which we pr...
Ofri Sadowsky, Jonathan D. Cohen, Russell H. Taylo