Vic forensics institute taps Monash Uni for ML ballistics

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Vic forensics institute taps Monash Uni for ML ballistics
Source: Monash University

For less invasive investigations.

Researchers at Monash University are looking to a range of digital technologies including augmented reality and machine learning to improve forensic ballistic analysis.

Working with the Victorian Institute of Forensic Medicine (VIFM) and the state coroner, the project seeks to help investigators track the trajectory of bullets and bullet fragments inside the human body, improving the quality of evidence and reducing the need for invasive post-mortems.

Using machine learning techniques and CT scans, the researchers plan to create a 3D model of the human anatomy, including entry and exit wounds, to produce accurate trajectory models and possibly assist in the determination of projectile calibre and the range from which it was fired.

Further developments could also support investigators in determining the type of gun used and whether the wounds were self-inflicted.

VIFM deputy director, Associate Professor Richard Bassed, said that ballistics in forensic medicine has traditionally involved “fairly basic” analytical techniques which haven’t changed significantly in 100 years.

“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,” he said.

“Trajectory was determined using basic techniques such as long probes to determine a projectile’s path.”

Even with new imaging available, Bassed said that current digital scans can’t differentiate between bullet fragments and foreign metal objects like a pacemaker of dental fillings - highlighting the need for more advanced solutions.

“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.”

Monash University’ lead for digital health, Professor Chis Bain, added that this approach is “much more scientific and rigorous” than what’s currently available, addressing recent calls for the improvement of 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,” he said.

“The technology could streamline workload and time efficiencies, and address any cultural sensitivities that may arise.”

Leidos Australia chief executive Christine Zeitz said that while faster and more accurate clinical decisions will improve outcomes for the sector, it also has other applications the company is interested in pursuing once the technology reaches maturity.

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

Leidos contributed $150,000 to the project through the Monash Institute of Medical Engineering.

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