Spinal fracture lesions segmentation based on U-net

Abstract

Because of the problem that the complexity of spine CT images, the irregular shape of vertebral boundary, low contrast, noise and unevenness in images, meanwhile there are artificial deviations and low efficiencies in clinic, which needs doctors' prior knowledge and clinical experience to determine lesions location in CT images, so it can not meet the clinical real-time needs. In this paper, We use deep learning to process the CT images of spine, and to divide lesions of (cervical fracture, cfracture), (thoracic fracture, tfracture), (lumbar fracture, lfracture) by the improved U-net[1]. The experiment shows that we can effectively segment spinal fracture lesions by U-net, which can basically meet the clinical real-time needs.