DRR acceleration using inexpensive GPUs for model-image registration based joint kinematic measurements.

ABSTRACT

Model-image registration methods are commonly used in research to measure three-dimensional joint kinematics from single-plane and bi-plane x-ray images. These methods have the potential to be beneficial if used clinically, but current techniques are too slow or expensive to be clinically practical. One technical element of these methods for measuring natural bone motion is the use of digitally reconstructed radiographs (DRRs). DRRs can be very expensive to compute, or require expensive and fast computer hardware. In this technical development, a numerically efficient Siddon-Jacobs algorithm for computing DRRs was implemented on a consumer-grade graphics card using a programming language for parallel architectures. Compared to traditional voxel projection algorithms with a central-processing-unit-only implementation, the parallel computation implementation on the graphics card provided speedups of 650-1546 times faster rendering, while retaining equivalent performance for joint kinematics measurements. The use of consumer grade graphics hardware may contribute to making model-image registration measurements of joint kinematics practical for clinical use.