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Melbourne uni researchers at the forefront of forensics technology

Wed, 9th Oct 2019
FYI, this story is more than a year old

Researchers at Monash University in Melbourne Australia are working with industry professionals to develop technology that will help forensic investigators to track bullet paths in shooting victims.

The technology, which utilises machine learning and augmented reality, could fundamentally transform ballistics investigations in Australia and on a global scale, according to a statement.

The University, along with industry partner Leidos, the Victorian Institute of Forensic Medicine (VIFM) and the state coroner are collaborating on this project.

The project aims to use machine learning to create a digital 3D model of the human anatomy, including entry and exit wounds. This will allow investigators to record the trajectory of the projectile through the body, identify and localise projectile fragments, and may one day be able to assist in determination of projectile calibre and the range from which the projectile was fired.

Leidos, the information technology and biomedical research company, has contributed $150,000 to the project. This contribution was made possible through the Monash Institute of Medical Engineering (MIME).

With further development and industry support, it could also help investigators determine the type of gun used, and if the wounds were self-inflicted or resulting from attempted homicide, according to the company.

Associate professor and deputy director of VIFM Richard Bassed says, “Ballistics in forensic medicine has traditionally involved fairly basic analytic techniques, which have not changed for a century.

“Before we had CT imaging, we were using x-rays to produce a 2D view of someone's body, which made localising projectiles and fragments difficult without conducting an internal examination. Trajectory was determined using basic techniques such as long probes to determine a projectiles path,” he says.

“Current imaging techniques can't differentiate between bullet fragments and foreign metal objects, such as a pacemaker or dental fillings.

“This technology will allow us to make a 3D digital reconstruction of a shooting victim that we can then slice in multiple planes and directions using advanced computer graphics, including the use of augmented reality. We can then apply machine learning to determine trajectory and projectile fragmentation, and create a 3D-printed model that can potentially be used as evidence in a court of law,” says Bassed.

Faculty of Information Technology professor of practice in digital health and Monash University lead for digital health, Chris Bain, says the project was just one example of how artificial intelligence and data science were transforming the digital health and forensic spaces.

“So, if we know the weapon and the damage its caused in the body, this technology could allow us to provide a more accurate representation of the range, distance and angle from which the bullet was fired,” he says.

“This approach is much more scientific and rigorous than the way this procedure is currently performed, and fits with recent calls for improved forensic examination practices.

“The big picture is that post-mortems could be reduced for shooting victims, as this technology has the potential to scan and analyse the body, as opposed to the body being dissected. The technology could streamline workload and time efficiencies, and address any cultural sensitivities that may arise,” says Bain.

Leidos Australia chief executive Christine Zeitz, says the group was proud to contribute to this groundbreaking research.

“The potential for this technology to influence the speed for making clinical decisions for better outcomes could be fundamental for the sector,” she says.

“We're also interested in how this research may influence the future development of health capability, particularly for our military and national security services,” says Zeitz.

This initiative is one of the ways Monash University is investigating in the development and use of AI and machine learning for social good through Monash Data Futures.

This University-wide institute is focused on key areas of health sciences, sustainable development, and better governance and policy in line with the University's core research pillars.

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