To efficiently and accurately describe the point-to-point correspondence of the bladder wall over all treatment fractions while preserving local topologies, we propose a novel graphic processing unit (GPU)-based non-rigid point matching algorithm.  The performance of the GPU-based TPS-RPM with local topology preservation algorithm (TPS-RPM-LTP) was evaluated using four numerically simulated synthetic bladders having known deformations, a custom-made porcine bladder phantom embedded with twenty one fiducial markers, and 29 fractional computed tomography (CT) images from seven cervical cancer patients.  This was achieved with a computational time of less than 15 s in all cases with GPU acceleration. 
GPU
The performance of the GPU-based TPS-RPM with local topology preservation algorithm (TPS-RPM-LTP) was evaluated using four numerically simulated synthetic bladders having known deformations, a custom-made porcine bladder phantom embedded with twenty one fiducial markers, and 29 fractional computed tomography (CT) images from seven cervical cancer patients. 
GPU-based TPS-RPM with local topology preservation algorithm (TPS-RPM-LTP)