1. A Novel Computer-Aided Method to Evaluate Scoliosis Curvature using Polynomial Math Function
- Author
-
Y Zhi-Han, J Cabrera-Escobar, A P Castro-Martin, HE Jiawei, V Romero-Rodríguez, M G Romero-Rodríguez, H Ying-Ying, M D Guamán-Lozada, and D F Guamán-Lozada
- Subjects
lcsh:Medical physics. Medical radiology. Nuclear medicine ,Polynomial ,scoliosis ,Radiological and Ultrasound Technology ,Cobb angle ,polynomial ,cobb-angle ,Intraclass correlation ,spinal curvatures ,lcsh:R895-920 ,Mathematical analysis ,Bioengineering ,Scoliosis ,medicine.disease ,CobB ,Curvature ,Pearson product-moment correlation coefficient ,methods ,symbols.namesake ,Spinal Curvatures ,symbols ,medicine ,Radiology, Nuclear Medicine and imaging ,Original Article ,Mathematics - Abstract
Background : Scoliosis is a health problem that causes a side-to-side curvature in the spine. The curvature may have an “S” or “C” shape. To evaluate scoliosis, the Cobb angle has been commonly used. However, digital image processing allows the Cobb angle to be obtained easily and quickly, several researchers have determined that Cobb angle contains high variations (errors) in the measurements. Therefore, a more reproducible computer aided-method to evaluate scoliosis is presented. Material and Methods: In this analytical study, several polynomial curves were fitted to the spine curvature (4 th to 8 th order) of thirty plain films of scoliosis patients to obtain the Curvature-Length of the spine. Each plain film was evaluated by 3 physician observers. Curvature was measured twice using the Cobb method and the proposed Curvature-Length Technique (CLT). Data were analyzed by a paired-sample Student t-test and Pearson correlation method using SPSS Statistics 25. Results: The curve of 7 th order polynomial had the best fit on the spine curvature and was also used for our proposed method (CLT) obtaining a significant positive correlation when compared to Cobb measurements (r=0.863, P
- Published
- 2019