3-D imaging and statistical analysis techniques could lead to a screening tool for autism among young children. The technique, which identifies facial measurements, could also provide clues to the condition’s genetic causes.
“We want to detect the specific facial traits of the face of a child with autism,” says Ye Duan, associate professor of computer science in the College of Engineering at the University of Missouri.
“Doing so might help us define the facial structures common to children with autism and potentially enable early screening for the disorder.”
Autism is a spectrum of closely related disorders diagnosed in patients who exhibit a shared core of symptoms, including delays in learning to communicate and interact socially.
Early detection of autism in children is the key for treatments to be most effective and produce the best outcomes.
Expanding upon previous studies using two-dimensional imaging, Duan, working with Judith Miles, professor emerita of child health-genetics in the Thompson Center for Autism and Neurodevelopmental Disorders, used a system of cameras to photograph and generate 3-D images of children’s faces.
