TY - JOUR
T1 - Automatic cobb angle determination from radiographic images
AU - Sardjono, Tri Arief
AU - Wilkinson, Michael H.F.
AU - Veldhuizen, Albert G.
AU - Van Ooijen, Peter M.A.
AU - Purnama, Ketut E.
AU - Verkerke, Gijsbertus J.
PY - 2013/9/15
Y1 - 2013/9/15
N2 - 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.
AB - 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.
KW - Cobb angle
KW - charged particle model
KW - curve fi tting
KW - deformable model
KW - radiograph
KW - scoliosis
KW - spinal curvature
UR - http://www.scopus.com/inward/record.url?scp=84884753618&partnerID=8YFLogxK
U2 - 10.1097/BRS.0b013e3182a0c7c3
DO - 10.1097/BRS.0b013e3182a0c7c3
M3 - Article
C2 - 23797500
AN - SCOPUS:84884753618
SN - 0362-2436
VL - 38
SP - E1256-E1262
JO - Spine
JF - Spine
IS - 20
ER -