Classification based on the presence of skull fractures on curved maximum intensity skull projections by means of deep learning

ConclusionClassification based on the existence of skull fractures on CMIPs with deep learning is feasible. For the purpose of pre-scanning PMCT data, a classification threshold of 0.75 with a sensitivity of 100% can be applied. A higher number of images of validated skull fractures available will increase the performance of the network. In the future, Deep learning might enable a more resource-efficient assessment in postmortem radiology.Graphical abstract
Source: Journal of Forensic Radiology and Imaging - Category: Radiology Source Type: research