WEST LAFAYETTE, Ind. Researchers are improving the performance of technologies ranging from medical CT scanners to digital cameras using a system of models to extract specific information from huge collections of data and then reconstructing images like a jigsaw puzzle.
The new approach is called model-based iterative reconstruction, or MBIR.
"It's more-or-less how humans solve problems by trial and error, assessing probability and discarding extraneous information," said Charles Bouman, Purdue University's Michael and Katherine Birck Professor of Electrical and Computer Engineering and a professor of biomedical engineering.
MBIR has been used in a new CT scanning technology that exposes patients to one-fourth the radiation of conventional CT scanners. In consumer electronics, a new camera has been introduced that allows the user to focus the picture after it has been taken.
"These innovations are the result of 20 years of research globally to develop iterative reconstruction," Bouman said. "We are just scratching the surface. As the research community builds more accurate models, we can extract more information to get better results."
In medical CT scanners, the reduction of radiation exposure is due to increased efficiency achieved via the models and algorithms. MBIR reduces "noise" in the data, providing greater clarity that allows the radiologist or radiological technician to scan the patient at a lower dosage, Bouman said.
"It's like having night-vision goggles," he said. "They enable you to see in very low light, just as MBIR allows you to take high-quality CT scans with a low-power X-ray source."
Researchers also have used the approach to improve the quality of images taken with an electron microscope. New findings are detailed in a research paper being presented during the Electronic Imaging 2013 conference in San Francisco this week.
Traditionally, imaging sensors and software
|Contact: Emil Venere|