Identification and Localization of Lumbar Intervertebral Discs on MRI Images with Faster RCNN

Abstract

Detection and identification of the anatomical structure of the human vertebrae is crucial for many tasks such as diagnosis of slipping and herniated discs. Recently many deep learning methods have been proposed to find automatically structure of vertebrae. Since there are very little vertebral images available in this area, end to end systems not feasible. In this paper, sequential phase based deep learning system used to detect and identify human lumbar discs from MRI. Every disc and every two neighbor discs are trained like Hidden Markov Model (HMM). System can detect and identify every lumbar disc in 0.5 seconds, with %89 accuracy and average 1.1 mm localization error. These results shows that proposed method can be comparable with state of art.