Slashdot Mirror
GPUs Helping To Lower CT Scan Radiation
Gwmaw writes with news out of the University of California, San Diego, on the use of GPUs to process CT scan data. Faster processing of noisy data allows doctors to lower the total radiation dose needed for a scan. "A new approach to processing X-ray data could lower by a factor of ten or more the amount of radiation patients receive during cone beam CT scans... With only 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. The reconstruction time ranged from 77 to 130 seconds on an NVIDIA Tesla C1060 GPU card, depending on the number of projections — an estimated 100 times faster than similar iterative reconstruction approaches... Compared to the currently widely used scanning protocol of about 360 projections with 0.4 mAs per projection, [the researcher] says the new processing method resulted in 36 to 72 times less radiation exposure for patients."
They said we'd use these processors for video games not medical technology
http://www.youtube.com/watch?v=o66twmBEMs0
But I want that mutation in the "rage center" of my brain!
The ideas is I turn into this huge green, angry thing (currently all I'm lacking is the green pigmentation).
Then it's BULK SMASH!
Chas - The one, the only.
THANK GOD!!!
so what processors are being used now - must be some DSP type. What is the processing power versus the GPU?
And start paying developers to make things in OpenCL instead of CUDA, or they're going to be quickly left behind.
It is by my will alone my thoughts acquire motion; it is by the juice of the coffee bean that the thoughts acquire speed
It's remarkable that high performance computing is driven by video games. So, legions of PC enthusiasts and uber-gamers, I salute you for your contributions to technology! P0wn on.
As usual in applying advances in medical (IT?) research, it won't be for at least 5-10 years before this reaches consumers. Might see it on House before then, of course.
So, they pump in all that radiation because the processor is too slow? Doesn't seem right to me. I would think if they could have simply put another $10000 into the machine (adding CPU cycles) to lower the required radiation they would have done that a long time ago. So is the use of a GPU just a side effect of some new technology that allows the machine to estimate or predict the image with a lower radiation dose? That GPUs are more effecient for some operations is nothing new - what's the real breakthrough here?
They (NVIDIA) say that you could have a very cheap supercomputer for just $10k, made with Nvidia GPUs only. Pretty impressed achievement, and btw they also say that their GPUs are in fact faster that the normal, Intel/AMD CPUs. I don't know about you, but once my piggy bank is full, i will get one of these super-computer monster.
Neat. Does this also reduce the running costs of the machines, or would that be a negligible benefit compared to not irradiating your patients?
Mercury Computer Systems has had this for 2 years now for CT and MRI. Re-inventing the wheel is awesome!
The official site: http://www.nvidia.com/object/tesla_computing_solutions.html And some price info (unofficial of course): http://nextbigfuture.com/2007/06/nvidia-tesla-supercomputer-for-1500-to.html
CT scanning is associated with an increased risk of cancer in children. This development will significantly lower that risk.
These patients are about to get RADIATION THERAPY. This CT scan will be delivered immediately before they are to receive a lethal radiation dose at the same location to kill their tumor. Reduction of dose in diagnostic CT (not cone-beam) is a much more valuable accomplishment.
This must be the first time anything associated with Tesla reduced radiation exposure....
Media that can be recorded and distributed can be recorded and distributed.
-kfg
Yeah yeah.. that's all fine and dandy, but how many FPS does it get in Crysis on ultra settings? (heh-heh)
Great. I had a CT this weekend. When I asked the technician how many Seivert of radiation I was being exposed to, she said "the lowest, if that's what you're worried about". Yes, that's what I'm worried about, and your answer didn't help me at all.
Does this now mean we can get more points on BOINC for finding ET?
the article and the original article, unfortunately, completely misses the point:
the reduced exposure time and processing time is essentially based on a rather new data processing technique called 'compressive sampling', or 'compressed sensing'.
it basically brings together data acquisition and data compression, namely such that the data compression is 'built-in' during the particular acquisition process.
Information is available on the net.
Some foreposters noticed that (iPhr0stByt3) in fact.
The use of GPU is only an obvious way to implement it for different resons.
@slashdot: completely missed the point (medical doctors anyway)
the reduced processing and data acquisition time is based on 'compressive sampling' or 'compressed sensing'.
The article completely misses the point !
Some posters noticed that already.
The reduced time has nothing to do with GPU's and blabla.
It is only an obvious implementation of this technique (applied to CT).
K.
This has been said elsewhere in this thread, the real breakthrough here is due to compressed sensing, but here are some extra information:
1- Compressed sensing basically used the idea that it is not necessary to sample an image (or a projection in this case) everywhere because natural data is fairly redundant. This is why you can capture a 10 Mpixel image in a digital camera and have it compressed to a 2 Mbyte JPEG file without losing much visible information. Compressed sensing basically does the compression *before* the sampling and not after. Researchers at Rice University for instance built a working, one-pixel camera using this brilliant principle.
2- Compressed (or compressive) sensing was proposed by Emmanuel Candes and Terence Tao respectively at Stanford and UCLA. Tao is a recent Fields medalist. I recommend reading his blog if you like mathematics.
3- This field is really less than 10 years old, it has completely turned on its head classical ideas about sampling-limited signal processing (Nyquist, Shannon, etc). It is a brilliant combination of signal, image processing and recent advances in combinatorial and convex optimization.
4- However this is only the beginning. Because compression happens before sampling, you need to make so-called sparsity assumptions about the signal ; in other words you need to know a great deal about what you are going to try to image. In interventional therapy, precise imaging of the patient is made beforehand in a classical way (CT or MRI), and this kind of technique is only used to make fine adjustments as therapy is ongoing. This is extremely useful and safe because of lower radiation output and because the physicians know what to expect.
5- Here the GPU is useful because it makes the processing fast enough to actually be used. It is an essential brick in the application, but of course not in the theory.
Best.
Congratulations! That's the most informative most I've ever seen on /. A very nice summary of a new field of research, and without jargon. What are you doing here?