George Mason University’s Injury Analytics Lab receives patent for AI bruise detection system

Body

Newly patented AI technology helps get bruise detection tools into the hands of clinicians, law enforcement, and researchers

Can new technology make it easier to understand bruises? That's the question researchers at George Mason University's Injury Analytics Lab (IAL) are answering with a patented technology that combines artificial intelligence, advanced imaging, and clinical data to give clinicians, forensic professionals, and researchers better information about skin injuries.

This technology reflects years of collaboration among experts in nursing, health informatics, and engineering, who worked together to transform research into a practical tool for injury assessment.

How the technology works

Image by College of Public Health.

The newly patented technology addresses current challenges in injury assessment by analyzing images of the skin alongside relevant clinical and demographic information from electronic health records. Similar to popular plant identification apps that combine image data with location information, the system uses AI to detect and assess bruise lesions.

"Documenting injuries accurately is essential for both medical treatment and seeking justice for victims of violence," said Associate Professor of Nursing and IAL Co-Director Katherine Scafide. "This patent recognizes our innovative approach that combines artificial intelligence, advanced imaging, and clinical data to help professionals make more informed decisions."

The patented artificial intelligence technology is built on a dedicated injury platform, which includes a large repository of injury images used by computer vision systems, and data from electronic health records that work together to support accurate injury assessment and real-world use. Development of the platform that hosts the data and systems, and related software is led by Professor of Health Informatics and IAL Co-Director Janusz Wojtusiak, while Professor of Engineering and IAL Co-Director David Lattanzi leads development of the computer vision systems and user-centered design.

One of the most innovative aspects of the patented technology is its ability to tailor imaging conditions such as light wavelength and camera filter to each individual.

Rather than relying on a standard lighting setup, the system can determine a person's skin color and select the most effective light wavelengths, filters, and imaging conditions for capturing injury evidence. By optimizing imaging for each person, the technology can improve injury detection and assessment across a wide range of skin tones, especially for people with darker skin tones, whose injuries can be harder to identify with traditional imaging.

But the technology goes beyond simply determining whether a bruise is present.

The system can estimate characteristics such as a bruise's age, size, color, and shape while also providing information about the confidence of its predictions. By combining visual data with information such as medical history, medications, demographics, and skin color, the technology can account for factors that influence how injuries appear, resulting in more accurate and reliable assessments than images alone.

Why the technology matters

Janusz Wojtusiak and Katherine Scafide in the Injury Analytics Lab. Photo provided

Bruises and other skin injuries have traditionally been difficult to identify and assess. Factors such as skin tone, lighting conditions, and the age of an injury can affect how visible an injury appears, creating challenges for clinicians, forensic professionals, and researchers.

This patented technology helps address those challenges by providing more objective, consistent injury assessments. More accurate documentation can help clinicians make informed treatment decisions, strengthen forensic evidence, support investigations, and give researchers better data to improve future care. By improving injury detection across diverse skin tones, the technology also has the potential to reduce disparities in how injuries are documented and evaluated.

It was also shaped by the needs of the professionals who will use it in real-world settings. "This technology is the result of a user-centric research process that included countless hours of interviews and workshops with health care providers and forensic professionals," explains Lattanzi. "These groups told us that they need easy-to-use tools that make documentation faster and more reliable. So that's exactly what we're building."

Built on years of research

The patented technology is supported by a library of more than 100,000 images of bruises and other skin characteristics collected through years of interdisciplinary research and collaboration.

The technology identifies and analyzes a wide range of skin features, including bruises, burns, scars, birthmarks, rashes, eczema, psoriasis, and other conditions. This extensive dataset helps train the system's deep-learning models and enables it to recognize patterns that may be difficult for the human eye to detect consistently.

Moving research into practice

The patent marks an important milestone in IAL's broader effort to develop evidence-based technologies that can improve injury assessment and documentation.

Beyond protecting the intellectual property behind the innovation, the patent creates opportunities for new partnerships, commercialization, and broader adoption of the technology. Researchers envision future applications that support health care providers, forensic specialists, law enforcement professionals, researchers, and patients through interfaces tailored to their specific needs.

As the technology continues to advance, the goal remains clear: transforming cutting-edge research into practical tools that improve accuracy, support equity, and help professionals make better-informed decisions when injury documentation matters most.

About the Injury Analytics Lab

Launched in 2026, George Mason University's IAL brings together researchers from clinical science, engineering, and health informatics to advance ongoing research focused on injury detection, assessment, and documentation. The lab serves as a hub for interdisciplinary projects that build on years of research to improve patient care, investigations, and legal proceedings.

IAL is directed by an interdisciplinary team including Katherine Scafide (School of Nursing, College of Public Health [CPH]), who leads the lab's clinical research; Janusz Wojtusiak (Department of Health Administration, Policy, and Informatics, CPH), who leads development of the injury platform and software systems; and David Lattanzi (Volgenau School of Engineering, College of Engineering and Computing), who leads development of the computer vision systems and user-centered design.