At Monash University in Melbourne Australia, researchers are working with industry professionals to develop technology that will help forensic investigators to track bullet paths in shooting victims. The technology utilizes machine learning and augmented reality, it could fundamentally transform ballistics investigations in Australia and on a global scale.
The University, along with industry partner Leidos, the Victorian Institute of Forensic Medicine (VIFM) and the state coroner are cooperating on this project. The project aims to use machine learning to create a digital 3D model of the human structure, including entry and exit wounds. This will allow investigators to record the route of the bullet through the body, identify and localize bullet fragments, and may one day be able to assist in determination of bullet caliber and the range from which the bullet was fired. An information technology and biomedical research company, Leidos, 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. Richard Bassed, Associate professor and deputy director of VIFM 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 localizing bullets and fragments difficult without conducting an internal examination. Trajectory was determined using basic techniques such as long probes to determine a bullets path. 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”