Research on detection method of lumbar disc herniation based on one-stage object detection

Today, medical and health care is playing an increasingly important role in people’s lives, the number of medical images increases rapidly, and the traditional manual diagnosis can’t meet the increasing demand of clinical diagnosis. It is the core of this research to realize the localization and classification of lesions by training a neural network, and to assist doctors in clinical diagnosis. Based on the one-stage object detection network FCOS, this paper improves the detection accuracy to a level comparable to the two-stage detection network while taking into account the detection speed and achieves a mAP of 0.664 on the MRI test set, which is higher than most existing networks. Overall, the proposed network has good performance in clinical assistance, and can be competent for some clinical application tasks of real-time detection.