Olson and Throne want their system to automate and refine the manual breast exam process. "Step one is to find a way to record accurate results," Olson said. "Step two is to use mathematical techniques to make a picture of what's going on inside the breast tissue in terms of stiffness."
Mammograms use X-rays, which are only sensitive to tissue density, not stiffness.
The new exam would look something like this: A woman lies on an exam table and a ring is placed around her breast; a robotic arm then performs the breast exam and measures how much force it takes and how much the tissue moves.
"This is how we imagine it's going to work, but for now we're just doing computer simulations of the process," Olson says.
To run these simulations quickly and to generate accurate results, Olson is applying the computational power of the resources at the Texas Advanced Computing Center (TACC) at The University of Texas at Austin.
"None of this would have been possible without the resources we used through TACC and XSEDE," Olson said, referring to the National Science Foundation-funded cyberinfrastructure that provides free advanced computing resources and time to researchers across the country. "By using supercomputers I can parallelize the job and finish simulations in minutes."
For the breast cancer research, speed of execution is very important, as a typical genetic algorithm must be iterated many times to produce a usable result for a complex problem. Olson is working with 2D and 3D algorithms to create a picture that represents the variations in tissue stiffness.
"It's quite promising," Olson said. "You can put a tumor about one centim
|Contact: Faith Singer-Villalobos|
University of Texas at Austin, Texas Advanced Computing Center