Computer vs human: Deep learning versus perceptual training for the detection of neck of femur fractures.

Introduction: To evaluate the accuracy of deep convolutional neural networks (DCNNs) for detecting neck of femur (NoF) fractures on radiographs, in comparison with perceptual training in medically-naïve individuals.

Methods: This study extends a previous study that conducted perceptual training in medically-naïve individuals for the detection of NoF fractures on a variety of dataset sizes. The same anteroposterior hip radiograph dataset was used to train two DCNNs (AlexNet and GoogLeNet) to detect NoF fractures.