Computer-aided Assessment of Scoliosis on Posteroanterior Radiographs

Overview

Journal Med Biol Eng Comput

Publisher Springer

Specialties Biomedical Engineering
Medical Informatics

Date 2009 Dec 17

PMID 20012376

Citations 23

Authors

Junhua Zhang

Edmond Lou

Douglas L Hill

James V Raso

Yuanyuan Wang

Lawrence H Le

Xinling Shi

Affiliations

Soon will be listed here.

Abstract

In order to reduce the observer variability in radiographic scoliosis assessment, a computer-aided system was developed. The system semi-automatically measured the Cobb angle and vertebral rotation on posteroanterior radiographs based on Hough transform and snake model, respectively. Both algorithms were integrated with the shape priors to improve the performance. The system was tested twice by each of three observers. The intraobserver and interobserver reliability analyses resulted in the intraclass correlation coefficients higher than 0.9 and 0.8 for Cobb measurement on 70 radiographs and rotation measurement on 156 vertebrae, respectively. Both the Cobb and rotation measurements resulted in the average intraobserver and interobserver errors less than 2 degrees and 3 degrees , respectively. There were no significant differences in the measurement variability between groups of curve location, curve magnitude, observer experience, and vertebra location. Compared with the documented results, measurement variability is reduced by using the developed system. This system can help orthopedic surgeons assess scoliosis more reliably.

Citing Articles

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Automatic Vertebral Rotation Angle Measurement of 3D Vertebrae Based on an Improved Transformer Network.

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Artificial Intelligence in Scoliosis: Current Applications and Future Directions.

Zhang H, Huang C, Wang D, Li K, Han X, Chen X J Clin Med. 2023; 12(23).

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Automatically measuring the Cobb angle and screening for scoliosis on chest radiograph with a novel artificial intelligence method.

Xie L, Zhang Q, He D, Wang Q, Fang Y, Ge T Am J Transl Res. 2022; 14(11):7880-7888.

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