Purdue University researchers have developed model-based iterative reconstruction (MBIR), an approach that can improve the performance of technologies using a system of models to extract specific information from huge collections of data and then reconstruct the images like a jigsaw puzzle.
"It's more or less how humans solve problems by trial and error, assessing probability and discarding extraneous information," says Purdue professor Charles Bouman.
MBIR has been used in a new computed tomography (CT) scanning technology that exposes patients to just 25 percent of the radiation of conventional CT scanners. The technology, called Veo, enables physicians to diagnose patients with high-clarity images and previously unattainable low radiation dose levels. "If you can get diagnostically usable scans at such low dosages this opens up the potential to do large-scale screening for things like lung cancer," Bouman notes.
Researchers also used MBIR to improve the quality of images taken with an electron microscope. "For electron microscopy, the principle advantage is higher resolutions, but there is also some advantage in reduction of electron dosage, which can damage the sample," Bouman says.
From Purdue University News
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