Detection of acute rib fractures on CT images with convolutional neural networks: effect of location and type of fracture and reader's experience.

Purpose: The evaluation of all ribs on thin-slice CT images is time consuming and it can be difficult to accurately assess the location and type of rib fracture in an emergency. The aim of our study was to develop and validate a convolutional neural network (CNN) algorithm for the detection of acute rib fractures on thoracic CT images and to investigate the effect of the CNN algorithm on radiologists' performance.

Methods: The dataset for development of a CNN consisted of 539 thoracic CT scans with 4906 acute rib fractures.