Detection of degenerative change in lateral projection cervical spine x-ray images

Degenerative changes to the cervical spine can be accompanied by neck pain, which can result from narrowing of the intervertebral disc space and growth of osteophytes. In a lateral x-ray image of the cervical spine, degenerative changes are characterized by vertebral bodies that have indistinct boundaries and limited spacing between vertebrae. In this paper, we present a machine learning approach to detect and localize degenerative changes in lateral x-ray images of the cervical spine. Starting from a user-supplied set of points in the center of each vertebral body, we fit a central spline, from which a region of interest is extracted and image features are computed. A Random Forest classifier labels regions as degenerative change or normal. Leave-one-out cross-validation studies performed on a dataset of 103 patients demonstrates performance of above 95% accuracy.

[1]  Rodney Long,et al.  Anterior osteophyte discrimination in lumbar vertebrae using size-invariant features. , 2004, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[2]  P. Côté,et al.  The Saskatchewan Health and Back Pain Survey: The Prevalence of Low Back Pain and Related Disability in Saskatchewan Adults , 1998, Spine.

[3]  P. Côté,et al.  The Saskatchewan Health and Back Pain Survey: The Prevalence of Neck Pain and Related Disability in Saskatchewan Adults , 1998, Spine.

[4]  Yuchou Chang,et al.  CBIR of Spine X-Ray Images on Inter-Vertebral Disc Space and Shape Profiles , 2008, 2008 21st IEEE International Symposium on Computer-Based Medical Systems.

[5]  L. Rodney Long,et al.  Identification and classification of spine vertebrae by automated methods , 2001, SPIE Medical Imaging.

[6]  F. Pernus,et al.  A review of methods for quantitative evaluation of spinal curvature , 2009, European Spine Journal.

[7]  John A. Davis,et al.  Degenerative disorders of the lumbar and cervical spine. , 2005, The Orthopedic clinics of North America.

[8]  Isam Abu-Qasmieh,et al.  Multi-class Multi-label Classification and Detection of Lumbar Intervertebral Disc Degeneration MR Images using Decision Tree Classifiers , 2013 .

[9]  Rodney Long,et al.  Image analysis techniques for characterizing disc space narrowing in cervical vertebrae interfaces. , 2004, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[10]  P. Brinckmann,et al.  Vertebral height, disc height, posteroanterior displacement and dens-atlas gap in the cervical spine: precision measurement protocol and normal data. , 2002, Clinical biomechanics.

[11]  A. G. Todd Cervical spine: degenerative conditions , 2011 .

[12]  Mohammed Benjelloun,et al.  A Framework of Vertebra Segmentation Using the Active Shape Model-Based Approach , 2011, Int. J. Biomed. Imaging.

[13]  Jason J. Corso,et al.  Computer-aided diagnosis of lumbar disc pathology from clinical lower spine MRI , 2010, International Journal of Computer Assisted Radiology and Surgery.

[14]  Mohammed Benjelloun,et al.  Fully automatic vertebra detection in x-ray images based on multi-class SVM , 2012, Medical Imaging.