Semi-automatic detection of cervical vertebrae in X-ray images using generalized hough transform

Vertebra detection presents the first step of any automatic spinal column diagnosis. This task becomes more difficult in the case of the cervical X-ray images characterized by their low contrasts and noise due to skull bones. In this paper, we describe an efficient modified template matching method for detecting cervical vertebrae using Generalized Hough Transform (GHT). The proposed method consists of three main steps toward vertebrae detection: 1) Offline training to obtain a robust average model of cervical vertebra. 2) Detecting the potential vertebra centers. 3) Adaptive Post-processing filter. X-ray Image data of 40 healthy cases were used to validate our approach by using a total of 200 cervical vertebrae. We obtained an accuracy of 89%.