Cervical spine mobility analysis on radiographs: a fully automatic approach

Abstract

Conventional X-ray radiography remains nowadays the most common method to analyze spinal mobility in two dimensions. Therefore, the objective of this paper is to develop a framework dedicated to the fully automatic cervical spine mobility analysis on X-ray images. To this aim, we propose an approach based on three main steps: fully automatic vertebra detection, vertebra segmentation and angular measurement. The accuracy of the method was assessed for a total of 245 vertebræ. For the vertebra detection, we proposed an adapted version of two descriptors, namely Scale-invariant Feature Transform (SIFT) and Speeded-up Robust Features (SURF), coupled with a multi-class Support Vector Machine (SVM) classifier. Vertebræ are successfully detected in 89.8% of cases and it is demonstrated that SURF slightly outperforms SIFT. The Active Shape Model approach was considered as a segmentation procedure. We observed that a statistical shape model specific to the vertebral level improves the results. Angular errors of cervical spine mobility are presented. We showed that these errors remain within the inter-operator variability of the reference method.