• Xing Huo, Jie Qing Tan, Jun Qian, Li Cheng, Jue Hua Jing, Kun Shao, and Bing Nan Li.
• Hefei University of Technology, Hefei, China.
• Comput. Biol. Med. 2017 Mar 1; 82: 111-118.

ObjectiveMeasuring the Cobb angle on computed tomography (CT) images remains a challenging but requisite task for clinical diagnoses of scoliosis. Traditionally, clinical practitioners resort to manual demarcation, but this approach is inefficient and subjective. Most of the existing computerized algorithms are two-dimensional (2D) and incapable of multi-angle calibration.MethodsA novel integrative framework based on curvature features and geometric constraints is proposed to measure three-dimensional (3D)Cobb angles on CT images. This framework enables Cobb angle estimation in stereo and accomplishes the synchronous computation of the Cobb angle in three imaging planes. The whole system was quantitatively evaluated on 22 spine models obtained from the clinic.ResultsThe results demonstrate that the integrative framework performs well in clinical Lenke classification and outperforms both the traditional manual method and the 2D digital method as evidenced by high intra-observer and inter-observer reliability (ICC>0.94, SEM 0.9°-1.2° for intra-observer, ICC>0.94, SEM 0.8°-1.2° for inter-observer). This 3D framework is also robust across different models (SE<3°).ConclusionsThe new integrative framework is able to measure the Cobb angles in three imaging planes simultaneously and is therefore clinically advantageous.Copyright © 2017 Elsevier Ltd. All rights reserved.

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