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 is more-or-less how humans solve problems by trial and error, assessing probability and discarding extraneous information," said Charles Bouman of the Purdue University.
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 is 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. Traditionally, imaging sensors and software are designed to detect and measure a particular property. The new approach does the inverse, collecting huge quantities of data and later culling specific information from this pool of information using specialized models and algorithms.
"We abandon the idea of purity – collecting precisely what we need," Bouman said. "Instead, let's take all the measurements we possibly can and then later extract what we want. This increases the envelope of what you can do enormously."
Researchers used MBIR to create Veo, a new CT scanning technology that enables physicians to diagnose patients with high-clarity images at previously unattainable low radiation dose levels. The technology has been shown to reduce radiation exposure by 78 percent.
"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 said. "You open up entirely new clinical applications because the dosage is so low."
A CT scanner is far better at diagnosing disease than planar X-rays because it provides a three-dimensional picture of the tissue. However, conventional CT scanners emit too much radiation to merit wider diagnostic use.
COMPAMED.de; Source: Purdue University