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. Here, the method is used to create a high-resolution 3-D electron microscopy reconstruction of aluminum nanoparticles, aiding efforts to design nanocomposites for applications ranging from fuel cells to transparent coatings.
Photo Credit: Purdue University, U.S. Air Force Research Laboratory and Carnegie Mellon University
Traditionally, imaging sensors and software are designed to detect and measure a particular property such as temperature. A new approach developed by researchers at Purdue University, West LaFayette, Ind., does the inverse, collecting huge quantities of data and later culling specific details from the pool of information using specialized models and algorithms.
The Purdue researchers say the methodology — called model-based iterative reconstruction — already is improving the performance of technologies ranging from medical CT scanners to digital cameras.
"It's more-or-less how humans solve problems by trial and error, assessing probability and discarding extraneous information," says Charles Bouman, Purdue University's Michael and Katherine Birck Professor of Electrical and Computer Engineering and a professor of biomedical engineering.
MBIR already has been used in a new CT scanning technology that exposes patients to one-fourth the radiation of conventional CT scanners. Purdue, the University of Notre Dame and GE Healthcare used MBIR to create Veo, a 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. 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 says. "We are just scratching the surface. As the research community builds more accurate models, we can extract more information to get better results."
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 says.
Improved resolution could help researchers design the next generation of nanocomposites for applications such as fuel cells and transparent coatings.
The research was authored by Purdue doctoral student Singanallur Venkatakrishnan; U.S. Air Force Research Laboratory researchers Lawrence Drummy and Jeff Simmons; Michael Jackson, a researcher from BlueQuartz Software; Carnegie Mellon University researcher Marc De Graef; and Bouman. A tutorial article also appeared in January in the journal Current Radiological Reports.
Future research includes work to use iterative reconstruction to study materials. Purdue is part of a new Multi-University Research Initiative funded by the U.S. Air Force and led by De Graef. Researchers will use the method to study the structure of materials, work that could lead to development of next-generation materials.