Collaborators from Mayo Clinic and IBM have exploited parallel computer architecture and memory bandwidth to dramatically speed the processing of 3-D medical images. The advance significantly aids image registration -- the computer-enhanced alignment in three-dimensional space of two medical images obtained at different dates or by using different imaging devices. With the images properly aligned over one another, a radiologist can more easily detect structural changes such as the growth or shrinkage of tumors.
"This alignment of images both improves the accuracy of interpretation and improves radiologist efficiency, particularly for diseases like cancer," says Bradley Erickson, M.D., Ph.D., Mayo Clinic radiology researcher.
Through porting and optimization of Mayo Clinic's Image Registration Application on the IBM BladeCenter® QS20 "Cell Blade," the application produced image results fifty times faster than the application running on a traditional processor configuration.
One way medical images are being improved is by using visual images from more than one source -- magnetic resonance imaging (MRI) and computerized tomography (CT) scans for example. The generation of computer-enhanced images from multiple sources must begin with accurate alignment of the visual data. When three dimensions and millions of pixels are involved, the task becomes exponentially complex. Within this scope, the need for higher processing speeds is essential.
For this imaging project, Mayo Clinic and IBM used 98 sets of images and ran the optimized registration application on the IBM BladeCenter QS20, in comparison with running the original application on a typical processor configuration. The application running on a typical processor configuration completed the registration of all 98 sets of images in approximately seven hours. The team adapted a "mutual-information-based" 3-D linear registration algorithm application optimized for Cell/B.E. and completed the registration for all 98 sets of images in just 516 seconds, with no registration taking more than 20 seconds.
The 3-D linear algorithm finds the best spatial positioning to maximize the amount of information gathered from the two images, thereby optimizing sampling quality while reducing sampling time. Greater efficiencies were achieved by caching data in cuboids or "bricks" so image sampling did not "waste" pixels. When sampling ratio was comparatively low, the team packed the sampled moving pixel images in a contiguous fashion (in an "image stripe") to speed retrieval when needed.
By running the application faster, a physician will be able to make a quicker diagnosis and promptly begin appropriate treatment for patients.
"This is all about taking technology innovation, collaborating with our customers, and applying it to help them directly benefit their patients," said Shahrokh Daijavad, Next Generation Computing, Systems & Technology, IBM. "This improvement with the application running on Cell will achieve two things -- allow for Mayo's doctors and radiologists to achieve in seconds what used to take hours, which in turn will significantly decrease the wait time and anxiety for a patient waiting on news from the doctor."
The results will be presented in full in a joint presentation by Mayo Clinic and IBM at the IEEE (Institute of Electrical and Electronics Engineers) International Symposium on Biomedical Imaging in Washington, D.C., April 12 to 15.
Materials provided by Mayo Clinic. Note: Content may be edited for style and length.
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