Hengyong Yu Is Developing Computer Program for New Generation of CT Scanners
09/28/2023
By Edwin L. Aguirre
Prof. Hengyong Yu of the Department of Electrical and Computer Engineering has been awarded a four-year, $2.3 million grant by the National Institutes of Health’s National Institute of Biomedical Imaging and Bioengineering to help improve the image quality and resolution of photon-counting computed tomography (CT) scans.
Yu’s research aims to enhance photon-counting CT scans by using the power of artificial intelligence technology for 3D color CT imaging.
“This technique fully utilizes the energy spectrum of the X-ray source and the energy-discriminating capability of the photon-counting detector,” says Yu, who is the project’s principal investigator. “This novel technology generates multienergy images at high spatial resolution, so it outperforms conventional CT imaging in characterizing soft tissues and contrast agents as well as pharmaceutical drugs.”
According to Yu, photon-counting CT offers not only fast, noise-free imaging but also lower dose of ionizing radiation compared with traditional CT scanners.
“This opens a new door to huge opportunities for imaging at functional, cellular and even molecular level, using novel contrast agents such as gold and bismuth nanoparticles,” he says.
Yu’s co-investigators are Profs. Yan Luo (electrical and computer engineering) and Yu Cao (computer science). Doctoral students Shuo Han and Bahareh Morovati are assisting Yu in lab research, and two additional Ph.D. students and a postdoctoral fellow will be joining the project.
External collaborators include Dr. Anthony Butler of MARS Bioimaging Ltd., a medical imaging company based in Christchurch, New Zealand, and Prof. Ge Wang of Rensselaer Polytechnic Institute.
The Power of CT Image Reconstruction
“With a photon-counting detector, when an X-ray passes through a patient’s body, multiple two-dimensional views can be obtained simultaneously for different X-ray energy channels,” notes Yu. “Similarly, images can be reconstructed for different energy channels, resulting in a colorful, 3D internal view of the body.”
Yu’s goal is to develop deep-learning algorithms and artificial neural networks that can automatically extract and analyze information or find hidden patterns from large amounts of data to reconstruct the images, despite having too few or low-dose X-ray views.
For this project, Yu is using a new photon-counting CT system that MARS Bioimaging had developed based on the Medipix detector licensed out of CERN, the European Organization for Nuclear Research. The detector can capture and process information from individual X-ray photons, producing 3D color images at very high resolution.
“We will demonstrate the clinical applications of the software we developed on a MARS photon-counting CT scanner,” Yu says. “Initially, the scanner will be used mainly to image hands and feet because of the limited detector size of the system. However, our software can be applied to other photon-counting CT scanners as well as other parts of the human body.”