A Semi-Automatic Algorithm for Estimating Cobb Angle

A Safari, H Parsaei, A Zamani, B Pourabbas

Abstract


Background: Scoliosis is the most common type of spinal deformity. A universal and standard method for evaluating scoliosis is Cobb angle measurement, but several studies have shown that there is intra- and inter- observer variation in measuring cobb angle manually.

Objective: Develop a computer- assisted system to decrease operator-dependent errors in Cobb angle measurement.

Methods: The spinal cord in the given x-ray image of the spine is highlighted using contract-stretching technique. The overall structural curvature of the spine is determined by a semi-automatic algorithm aided by the operator. Once the morphologic curve of the spine is determined, in the last step the cobb-angle is estimated by calculating the angle between two normal lines to the spinal curve at the inflection points of the curve.

Results: Evaluation results of the developed algorithms using 14 radiographs of patients ( 4 - 40 years old) with cobb angle ranges from 34 - 82 degrees, revealed that the developed algorithm accurately estimated cobb angle. Statistical analysis showed that average angle values estimated using the developed method and that provided by experts are statistically equal. The correlation coefficient between the angle values estimated using the developed algorithm and those provided by the expert is 0.81.

Conclusion: Compared with previous algorithms, the developed system is easy to use, less operator-dependent, accurate, and reliable. The obtained results are promising and show that the developed computer-based system could be used to quantify scoliosis by measuring Cobb angle.


Keywords


Cobb-angle Measurement, Curve-fitting, Scoliosis, Spinal Curvature Measurement

Full Text:

PDF


DOI: https://doi.org/10.22086/jbpe.v0i0.730

eISSN: 2251-7200        JBPE NLM ID: 101589641

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License.

Indexing:  PubMed Central, Scopus, EMBASE, EBSCO, DOAJIndex CopernicusISCSIDGoogle scholar, Open J-Gate, Geneva Free Medical Journals, EMRmedexBarakatkns, Magiran, HINARI, Electronic Journals Library