Modelling approach could improve imaging technologies
6 Feb 2013
Researchers are improving imaging techniques using a model-based iterative approach called MBIR.
MBIR uses a system of models to extract specific information from huge collections of data and then reconstruct images like a jigsaw puzzle.
“It’s more-or-less how humans solve problems by trial and error, assessing probability and discarding extraneous information,” said Charles Bouman at Purdue University.
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 specialised 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.”
Purdue, the University of Notre Dame and GE Healthcare 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.
“But as the dosage goes down, the risk-benefit tradeoff for screening will become much more favorable,” Bouman said. “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.”
In the electron microscope research, MBIR was used to take images of tiny beads called aluminum nanoparticles.
“We are getting reconstruction quality that’s dramatically better than was possible before, and we think we can improve it even further,” Bouman said.
Improved resolution could help researchers design the next generation of nanocomposites for applications such as fuel cells and transparent coatings.
