Pittsburgh-based Duquesne University says its students’ recent design of drones for pothole detection incorporates the same skill set used in the detection of cancerous cells.
Undergraduate biomedical engineering students recently built a 3D-printed quadcopter with a construction that propels it forward as it captures GPS coordinates corresponding with camera images of potholes, according to the university, which adds that both pothole images and cancerous-cell images are irregularly shaped and are detected based on geometric patterns.
Dr. John Viator, director of Duquesne’s biomedical engineering program, says the drone is designed to differentiate between a pothole and manhole, a pothole and speed bump, and a pothole and new asphalt.
Regarding its relation to cancer-cell detection, Viator says, “You use the same skill set – shape analysis – to identify tumors in an MRI or to identify pathological cells in blood samples. It’s an active area in research.”
The students’ drone, says Duquesne, delivers information through software the team developed to share geospatial coordinates along with the camera image.
According to the university, image processing is at the intersection of engineering technology and the medical arena. These students are also demonstrating how cells in a blood sample look the same in a computer-generated image, whether they are cancer cells or typical cells. With their software, students can assign gradient colors based on non-visible pigmentation differences in specialized areas of the cell and its edges. The program produces a rainbow-colored version of the cell images – showing which cells are cancerous.
“The drone was an entryway to pursue and make a contribution to research and their careers,” Viator explains.