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George Mason University receives a nearly $5M gift to help the advancement in domestic violence research

New tech will work five times better than a white light, assisting forensic nurses and law enforcement to identify and visualize bruising on all skin tones.

FAIRFAX, Va. — George Mason University announced an anonymous gift of $4.85 million to advance groundbreaking research on bruise and injury detection. The funding will help develop new tools in imaging technology. The new tech will work five times better than a white light, assisting forensic nurses, social service providers, and law enforcement to identify and visualize bruising across all skin tones. 

“A gift of this magnitude brings transformative resources to Mason’s cross-disciplinary research and collaborative approach that takes ground-breaking research to new heights with the potential for greater use and impact,” said Melissa J. Perry, dean of the College of Public Health.

The funding will expand the team’s bruise detection system that leverages artificial intelligence (AI), imaging and light technologies, forensic reports, and clinical expertise to increase data collection and access to care for trauma victims. 

One in three women worldwide experience physical abuse from either a stranger or significant other. More than 10 million men and women experience domestic violence nationwide each year. 

“In a nation where domestic violence disproportionately impacts communities of color, this innovative research holds immense promise.” Ruth Glenn, president of Survivor Justice Action, said. “By prioritizing inclusivity and recognizing the unique challenges faced by survivors with darker skin tones, Scafide’s research aligns seamlessly with our vision to end domestic violence in our lifetime.” 

Bruises and soft tissue trauma tend to be the most reported. When injuries are properly documented, survivors are more likely to pursue criminal charges against their abuser. 

"A vital piece to success is ensuring that any AI tool has access to in-depth data from all skin tones and skin characteristics alongside human expert analysis,” said Lattanzi, an associate professor in the Department of Civil, Environmental, and Infrastructure Engineering in the College of Engineering and Computing.

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