Global Localization and Orientation of the Cervical Spine in X-ray Imaging

Al-Arif, S. M., Gundry, M., Slabaugh, G.G. & Knapp, K. (2016). Global Localization and Orientation of the Cervical Spine in X-ray Imaging. Paper presented at the Computational Methods and Clinical Applications for Spine Imaging, 17 Oct 2016, Athens, Greece.

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Abstract

Injuries in cervical spine X-ray images are often missed by emergency physicians. Many of these missing injuries cause further complications. Automated analysis of the images has the potential to reduce the chance of missing injuries. Towards this goal, this paper proposes an automatic localization of the spinal column in cervical spine X-ray images. The framework employs a random classification forest algorithm with a kernel density estimation-based voting accumulation method to localize the spinal column and to detect the orientation. The algorithm has been evaluated with 90 emergency room X-ray images and has achieved an average detection accuracy of 91% and an orientation error of 3.6◦. The framework can be used to narrow the search area for other advanced injury detection systems.

Item Type: Conference or Workshop Item (Paper)
Additional Information: The final publication will be available at Springer via http://www.springer.com/gb/computer-science/lncs
Uncontrolled Keywords: Random forest, Classification, Cervical, Vertebra, Localization, Orientation
Divisions: School of Informatics > Department of Computing
URI: http://openaccess.city.ac.uk/id/eprint/15480

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