Spine localization in X-ray images using interest point detection

Abstract

This study was conducted to evaluate a new method used to calculate vertebra orientation in medical x-ray images. The goal of this work is to develop an x-ray image segmentation approach used to identify the location and the orientation of the cervical vertebrae in medical images. We propose a method for localization of vertebrae by extracting the anterior-left-faces of vertebra contours. This approach is based on automatic corner points of interest detection. For this task, we use the Harris corner detector. The final goal is to determine vertebral motion induced by their movement between two or several positions. The proposed system proceeds in several phases as follows: (a) image acquisition, (b) corner detection, (c) extracting of the corners belonging to vertebra left sides, (d) global estimation of the spine curvature, and (e) anterior face vertebra detection.

Fig 1

(a) Flexion, neutral, and extension position of the cervical spine; (b) vertebra anterior face extracted using a contour detection process.

Fig 2

Corner detection results using the Harris detector, applied to three images of the same patient, in three different positions, (a): neutral, (b): extension, (c): flexion.

Fig 3

(a) Detection of the two first anterior face corners using the click point position; (b) the first line established and the tangent at mid line used to iterate the research at the two directions: up and bottom.

Fig 4

(a) The research circle used to extract the third corner through the first tangent; (b) the third and the fourth corners extracted using the first tangent. A tangent is traced through each of these new corners for extracting new ones in the two directions: bottom and up.

Fig 5

Anterior faces corner extraction progress, (a): extraction of new corner 4 and 5, (b): extraction of new corners 6 and 7.

Fig 6

Anterior faces corner extraction progress, (a): extraction of new corner 8 and 9; (b): extraction of new corners 10 and 11.

Fig 7

Adding a virtual anterior face corner—if this one is not detected.

Fig 8

Anterior face detection results —using the proposed method— applied to three images of the cervical spinal column, corresponding to Figure 2. (a): neutral position, (b): extension position, (c): flexion position.

Fig 9

The global curvature of the cervical spinal column, (a): neutral position, (b): extension position, (c): flexion position.

Fig 10

Angular variation between the positions of extension and flexion using the proposed method.

Fig 11

Other examples of the global spine curvature detection. These images are representing the cervical spinal column of different patients: (a), (c), and (e): extension positions, (b), and (d) neutral positions, (f): extension position.