Safely train next generation of X-ray technologists
Imagine taking an X-Ray…without taking an X-Ray.
Seems counterintuitive, but that is what innovators from UNMC sought to do. They developed an X-Ray Output Simulator that produces a unique, realistic simulated x-ray image that pairs with actual radiographic equipment. The simulator limits technologist error in patient positioning, which leads to repeated X-ray images of patients.
To learn radiographic positioning skills, radiology students work with each other manipulating actual radiographic equipment, but they cannot take X-Rays of each other to limit radiation exposure.
As a result, students can’t see the results of their applied positioning skills until working with patients during clinical rotations. Students also can’t evaluate their work or think through correcting errors without an X-Ray image.
This new technology changes everything. Students manipulate actual radiographic equipment and take a simulated X-Ray image to test their skills without the danger of radiation.
Developed by UNMC radiology instructor Ellie Miller, and electrical engineer Eric Psota, PhD, the technology consists of cameras that capture information about the live human model’s anatomic landmarks, and simulates an X-ray image using a deep machine learning algorithm.
Trainees can use this system to practice patient positioning skills on a live human model to critique applied radiographic positioning skills, critically think through positioning errors, and conceptualize relationships between anatomy and patient positioning. Because there isn’t any radiation exposure, a licensed technologist does not need to be present, allowing for independent student practice.
To discuss licensing opportunities contact Lisa Carlson, PhD, at firstname.lastname@example.org or 402-315-0543.