An international team led by researchers at the Open University of Catalonia (UOC) in Spain has developed a new method that improves the quality of the images obtained from CT scans. The algorithm, which has been tested on simulated data, enables them to better distinguish different body tissue types and opens the door to lowering the doses of radiation to which patients are exposed during this type of test.

The team led by Mohammad Mahdi Dehshibi, PhD, of the Pattern Research Centre in Tehran, Iran, who is a postdoctoral researcher at the UOC’s Scene Understanding and Artificial Intelligence laboratory, has developed a new post-processing algorithm which increases the quality of reconstructed CT images. While conventional CT methods pick up only a part of the x-ray energy spectrum, the researchers tested a broader energy range, divided into intervals, to reach higher contrast. After testing it on constructed data using GATE/GEANT4 simulation software, they found that the algorithm enhances the quality of the images while reducing noise, which enables better discrimination between different types of tissue with lower doses of x-rays.

“Distinguishing between two different tissues (either normal or abnormal ones) in the same region is critical for physicians or radiologists to plan for further treatments, where this decision is dealing with the patients’ lives,” Dehshibi says.  “Having better tissue discrimination increases the success rate of the medicine’s plan.”  The new method increases the capacity to distinguish between tissues by 60% in simulations compared to conventional CT.

“Our viewpoint was proposing a post-processing approach that does not need a substantial hardware reconfiguration and gives more freedom to imaging scientists for further exploration,” Dehshibi says. “We hope that the findings of this study are later examined in the clinical setting to reduce the radioactive effect of irradiating with X-ray.”

Read more from Open University of Catalonia and find the paper in Journal of Information Processing.

Featured image: National Cancer Institute /