Optimising image and PMCT databases for research at the Victorian Institute of Forensic Medicine
online resource
posted on 2018-03-29, 02:31authored byRichard Bassed
70,000 CT full body scans and multiple high resolution optical photographs associated with each case. This PM-CT database sits alongside a case management system (iCMS) that can currently be searched for keyword causes of death. The opportunities for the application of techniques such as deep learning to facilitate the answering of important research questions is extensive and has important medico-legal consequences. The VIFM is looking for expressions of interest from research groups that can partner in grant applications to provide PhD students and post-doctoral candidates to help use artificial intelligence to solve image analysis, classification and measurement problems associated with our post-mortem databases. The Victorian Institute of Forensic Medicine (VIFM) is tasked with performing the medical investigations and ancillary tests relating to all deaths reported to the Victorian State Coroner. As a part of this investigation process various data is collected, including photographic imagery and CT scan data for every case. Part of the remit for the VIFM is to conduct forensic medical research – learning from the dead to benefit the living. The VIFM now has one of the world’s largest post-mortem computed tomography (PM-CT) databases containing > 70,000 CT full body scans and multiple high resolution optical photographs associated with each case. This PM-CT database sits alongside a case management system (iCMS) that can currently be searched for keyword causes of death. The opportunities for the application of techniques such as deep learning to facilitate the answering of important research questions is extensive and has important medico-legal consequences. The VIFM is looking for expressions of interest from research groups that can partner in grant applications to provide PhD students and post-doctoral candidates to help use artificial intelligence to solve image analysis, classification and measurement problems associated with our post-mortem databases.