Center for Laser Applications

Medical Imaging

Medical Imaging (MI) technology is revolutionizing medical diagnosis and treatment by enabling early, accurate, non-invasive detection of diseases.  As a result, treatments can be targeted, less traumatic for the patient, and less expensive to perform than in the past.  Many of the most effective and widely used MI methods use electromagnetic radiation (such as x-rays, gamma rays or radio frequencies) to detect and characterize living tissue in-vivo.  Healthy and diseased tissue can be identified and precisely located from the images. 

The MI research group is led by Professor Jacqueline Johnson in the Biomedical Research section of UTSI’s Center for Laser Applications.  The research broadly covers detectors, sensors and imaging technologies.  The current focus is on next-generation x-ray imaging technology that can provide superior resolution, require small x-ray exposures, and enable fast, low-cost screening for use in mammography, pediatrics and other areas.  The work is mainly supported by the National Institutes of Health.  The novel sensors use europium ions that are “embedded” in specialized glass ceramics to store x-ray images like a reusable film.  The materials are formed to shape as glass and then processed to make x-ray sensitive plates.  The image plates are “read” with a scanning laser and then images are stored and analyzed using a computer.  In addition to the UTSI group, the research team includes scientists and engineers from SUNY (Stony Brook), the Fraunhofer Institute in Halle, Germany, Argonne National Laboratory, and a small business partner www.matsdev.com that is helping to commercialize the new technologies. 

Potential non-medical applications of the imaging technology are in non-destructive testing of critical components for aerospace systems and sensitive broad spectrum radiation detectors.    

X-ray micro-computed tomography images of a mouse digital joint.  The image was made using a europium doped glass-ceramic image plate. 

(a) transmission image (b) reconstructed 3-D image of selected region(c) cross-section of image