As the decade of 3-D kicks off, next one decade will revolve around the applications of the new technology in many more fields from Shahrukh Khan’s 3D statue to International Space Station need for a ranch.
Not far behind, health scientists have found that advanced 3-D facial imaging will help detect early symptoms of autism in kids.
The University of Missouri researchers’ team came up with its new study based on the use of advanced three-dimensional imaging and statistical analysis techniques to identify autism in children by measuring facial angles. Soon 3D may become an effective tool to screen young children for autism and it may provide clues to its genetic causes too, say scientists.
“We want to detect the specific facial traits of the face of a child with autism,” said Ye Duan from the College of Engineering at the University of Missouri. It might “help us define the facial structures common to children with autism and potentially enable early screening for the disorder,” Duan said.
Duan and co-author Judith Miles, professor emeritus in the MU Thompson Center for Autism and Neurodevelopmental Disorders, used a system of cameras to generate three-dimensional images of children’s faces aged between 8 and 12 years.
One group of children had been already diagnosed with autism by the Thompson Centre and the other group consisted of typically developing children. Taking their photoes, developing them in a 3D form, researchers were able to measure distances along the curvature of the face rather than in a straight line as had been done in previous tests.
Duan then applied a modern statistical analysis tool to measure minute differences in the facial curves and measurements of each group.
“Over years of treating children, I noticed that a portion of those diagnosed with autism tend to look alike with similar facial characteristics,” Miles said. “I thought perhaps there was something more than coincidence at play.”
The differences my not be abnormal but appeared analogous to similarities observed among siblings, he said and added that using three-dimensional images and statistical analysis, the team was able to “create a ‘fine-tuned map’ of children’s faces and compared those measurements to the various symptoms they exhibit.”
The researchers came out with three distinct subgroups of children with autism who had similar measurement patterns in their facial features and they also shared similarities in the type and severity of their autism symptoms.
The study has been published in the Journal of Autism and Developmental Disorders.