Accelerating colonic polyp detection using commodity graphics hardware

We present a parallel implementation of an algorithm for the detection of colonic polyps from CT data sets. This implementation is designed specifically to take advantage of the computational power available on modern Graphics Processing Units (GPUs), which significantly reduces the execution time to streamline the workflow of clinicians examining the data. We provide details about the changes which were made to the existing algorithm to suit the new target hardware, and perform tests which demonstrate that the results are a very close match to the reference implementation while being computed in a fraction of the time.