CFP last date
20 May 2024
Reseach Article

Cobb Angle Quantification for Scoliosis using Image Processing Techniques

Published on April 2012 by Raka Kundu, Prasanna Lenka, Amlan Chakrabarti
International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
Foundation of Computer Science USA
IRAFIT - Number 5
April 2012
Authors: Raka Kundu, Prasanna Lenka, Amlan Chakrabarti
2a191dfb-eecf-453b-adcb-9228725a5f03

Raka Kundu, Prasanna Lenka, Amlan Chakrabarti . Cobb Angle Quantification for Scoliosis using Image Processing Techniques. International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012). IRAFIT, 5 (April 2012), 6-10.

@article{
author = { Raka Kundu, Prasanna Lenka, Amlan Chakrabarti },
title = { Cobb Angle Quantification for Scoliosis using Image Processing Techniques },
journal = { International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012) },
issue_date = { April 2012 },
volume = { IRAFIT },
number = { 5 },
month = { April },
year = { 2012 },
issn = 0975-8887,
pages = { 6-10 },
numpages = 5,
url = { /proceedings/irafit/number5/5878-1034/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
%A Raka Kundu
%A Prasanna Lenka
%A Amlan Chakrabarti
%T Cobb Angle Quantification for Scoliosis using Image Processing Techniques
%J International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
%@ 0975-8887
%V IRAFIT
%N 5
%P 6-10
%D 2012
%I International Journal of Computer Applications
Abstract

Measurement of Cobb angle is the standard technique used for scoliosis assessment. The challenging task in computerized method lies in totally automating the method of curvature measurement from digital X-ray images. In this paper we presented a method which automatically measures the Cobb angle from radiographs after selection of the end vertebrae of the curve. The image processing methods used shows an appreciable measurement of scoliosis curvature in digital X-ray image, reducing user intervention. The proposed method detects the inclination of the vertebra by identifying the lines of the endplate from edge image, helping in calculating the Cobb angle in the direction of the endplates automatically. An intra-observer and inter-observer assessment was performed over the radiographs using the manual and the proposed digital method. A level of improvement for Cobb angle measurement is achieved in the proposed computerized image processing technique in terms of estimating the vertebral slope and limiting user intervention.

References
  1. Eeuwijk A. H. W. V., Lobregt S., Gerritsen F. A. 2006 A novel method for digital X-ray imaging of the complete spine.
  2. Chockalingam N., Dangerfield P. H., Giakas G., Cochrane T., Dorgan J. C. 2002 Computer-assisted cobb measurement of scoliosis. Eur Spine J 11: 353-357.
  3. Gstoettner M., Sekyra K., Walochnik N., Winter P., Wachter R., Bach C. M. 2007 Inter-and intraobserver Reliability assessment of the cob angle: manual versus digital measurement tools. Eur Spine J 16: 1587-1592.
  4. Allen S., Parent E., Khorasani M., Hill D. L., Lou E., Raso J. V., 2008 Validity and Reliability of Active Shape Models for the Estimation of Cobb Angle in Patients with Adolescent Idiopathic Scoliosis, Journal of Digital Imaging,Vol 21, No 2, 208-218.
  5. Tanure M. C., Pinheiro A. P., Oliveira A. S., 2010 Reliability assessment of Cobb angle measurements using manual and digital methods. The Spine Journal 10: 769- 774.
  6. Zhang J., Lou E., Le L. H., Hill D. L., Raso J. V., Wang Y., 2009 Automatic Cobb Measurement of Scoliosis Based on Fuzzy Hough Transform with Vertebral Shape Prior, Journal of Digital Imaging, Vol 22. No 5: 463-472.
  7. Gonzalez, R.C., R.E. Woods, Digital Image Processing, Publisher – Pearson Education.
  8. Maini R., Aggarwal H., Study and Comparison of Various Image Edge Detection Techniques. International Journal of Image Processing, Vol. (3): Issue (1)
  9. Daghameen K., Arman N., 2007 An Efficient Algorithm For Line Recognition Based on Integer Arithmetic.
  10. Lee K., 2006 Application of the Hough transform, University of Massachusetts, Lowell.
  11. Duda R. O., Hart P. E., 1972 Use of the Hough transform to detect lines and curves in pictures, Published in the Comm. ACM, Vol 15, No. 1: 11-15.
  12. Shea K.G., Stevens P. M., Nelson M., Smith J. T., 1998 Masters K. S., Yandow S., A comparison of manual versus computer-assisted radiographic measurement. Intraobserver measurement variability for Cobb angles, Spine, 23(5):551-5.
  13. Wills B. P. D., Auerbach J. D., Zhu X., Caird M. S., Horn B. D., Flynn J. M., Drummond D. S., Dormans J. P., Ecker M. L., 2007 Comparison of Cobb angle measurement of scoliosis radiographs with preselected end vertebrae: traditional versus digital acquisition, Spine, 32(1):98-105.
  14. Mezghani N., Phan P., Mitiche A., Labelle H., Guise J. D., 2010 A computer-aided method for scoliosis fusion level selection by a topologicaly ordered self organizing Kohonen network. International Conference on Pattern Recognition, IEEE Computer Society.
  15. Chen W., Edmond H., M., Le L., H., 2011 Using Ultrasound Imaging to Identify Landmarks in Vertebra Models to Assess Spinal Deformity. 33rd Annual International Conference of the IEEE EMBS.
  16. Xu Z., Pan J., Zhang S., 2007 A Novel Automatic Framework for Scoliosis X-Ray Image Retrieval. Proceedings of International Joint Conference on Neural Networks.
Index Terms

Computer Science
Information Sciences

Keywords

Image Processing Digital X-ray Image Scoliosis Cobb Angle