Points of interest detection in cervical spine radiographs by polygonal approximation

Abstract

In this paper, we introduce a robust approach to detect points of interest in cervical spine radiographs. The perspective of this work is to segment the vertebrae on X-Ray images for the analysis of the vertebral mobility. In previous work, we proposed a segmentation technique based on Active Shape Model. The extraction and the detection of the vertebra corners can contribute to the automatic initialization of the Active Shape Model search and can give valuable information about the spine curvature. Here, we present the benefits of the polygonal approximation dedicated to the points of interest detection. The methodology developed here is composed of 3 stages: a contrast limited adaptive histogram equalization, a Canny edge detection filter and an edge polygonal approximation. The first histogram equalization step is a pretraitment needed to improve the image quality in order to perform a better contour detection. The Canny operator detects the edges in the radiograph which are used as an input to the polygonal approximation. The edges become segment lines whose intersections define corners. We compare the results obtained with our approach based on the polygonal approximation to results coming from the Harris corner detector.