Automatic cobb angle determination from radiographic images

Tri Arief Sardjono*, Michael H.F. Wilkinson, Albert G. Veldhuizen, Peter M.A. Van Ooijen, Ketut E. Purnama, Gijsbertus J. Verkerke

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

66 Citations (Scopus)

Abstract

STUDY DESIGN.: Automatic measurement of Cobb angle in patients with scoliosis. OBJECTIVE.: To test the accuracy of an automatic Cobb angle determination method from frontal radiographical images. SUMMARY OF BACKGROUND DATA.: Thirty-six frontal radiographical images of patients with scoliosis. METHODS.: A modified charged particle model is used to determine the curvature on radiographical spinal images. Three curve fitting methods, piece-wise linear, splines, and polynomials, each with 3 variants were used and evaluated for the best fit. The Cobb angle was calculated out of these curve fit lines and compared with a manually determined Cobb angle. The best-automated method is determined on the basis of the lowest mean absolute error and standard deviation, and the highest R. RESULTS.: The error of the manual Cobb angle determination among the 3 observers, determined as the mean of the standard deviations of all sets of measurements, was 3.37 . For the automatic method, the best piece-wise linear method is the 3-segments method. The best spline method is the 10-steps method. The best polynomial method is poly 6. Overall, the best automatic methods are the piece-wise linear method using 3 segments and the polynomial method using poly 6, with a mean absolute error of 4,26 and 3,91 a standard deviation of 3,44 and 3,60 , and a R of 0.9124 and 0.9175. The standard measurement error is significantly lower than the upper bound found in the literature (11.8 ). CONCLUSION.: The automatic Cobb angle method seemed to be better than the manual methods described in the literature. The piece-wise linear method using 3 segments and the polynomial method using poly 6 yield the 2 best results because the mean absolute error, standard deviation, and R are the best of all methods.

Original languageEnglish
Pages (from-to)E1256-E1262
JournalSpine
Volume38
Issue number20
DOIs
Publication statusPublished - 15 Sept 2013

Keywords

  • Cobb angle
  • charged particle model
  • curve fi tting
  • deformable model
  • radiograph
  • scoliosis
  • spinal curvature

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