Cone beam CT is important in image-guided radiation therapy (IGRT), a state-of-the-art cancer treatment.
The method uses repeated scans during a course of radiation therapy to precisely target tumours and minimise radiation damage in surrounding tissue.
While it is really successful, repeated scans require huge doses of radiation, which are not a good thing.
Reducing the total number of X-ray projections and the mAs level per projection (by tuning down the X-ray generator pulse rate, pulse duration and/or current) during a CT scan can help minimize patient’s exposure to radiation.
However this creates mathematically incomplete data that takes hours to process using the current iterative reconstruction approaches.
Xun Jia, a University of California scientist, developed a CT reconstruction algorithm for the Tesla GPU.
Since Tesla processes data in parallel it can reconstruct a cone beam CT scan in about two minutes. Using 20 to 40 total number of X-ray projections and 0.1 mAs per projection, the team achieved images clear enough for image-guided radiation therapy.
This worked out 100 times faster than similar iterative reconstruction approaches and makes the radiation therapy safer.
Your average body gets 36 to 72 times less radiation exposure and is more likely to get better.