Improving vertebra segmentation through joint vertebra-rib atlases

Yinong Wang; Jianhua Yao; Holger R. Roth; Joseph E. Burns; Ronald M. Summers

doi:10.1117/12.2217118

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24 March 2016 Improving vertebra segmentation through joint vertebra-rib atlases

Yinong Wang, Jianhua Yao, Holger R. Roth, Joseph E. Burns, Ronald M. Summers

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Proceedings Volume 9785, Medical Imaging 2016: Computer-Aided Diagnosis; 97853O (2016) https://doi.org/10.1117/12.2217118
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Accurate spine segmentation allows for improved identification and quantitative characterization of abnormalities of the vertebra, such as vertebral fractures. However, in existing automated vertebra segmentation methods on computed tomography (CT) images, leakage into nearby bones such as ribs occurs due to the close proximity of these visibly intense structures in a 3D CT volume. To reduce this error, we propose the use of joint vertebra-rib atlases to improve the segmentation of vertebrae via multi-atlas joint label fusion. Segmentation was performed and evaluated on CTs containing 106 thoracic and lumbar vertebrae from 10 pathological and traumatic spine patients on an individual vertebra level basis. Vertebra atlases produced errors where the segmentation leaked into the ribs. The use of joint vertebra-rib atlases produced a statistically significant increase in the Dice coefficient from 92.5 ± 3.1% to 93.8 ± 2.1% for the left and right transverse processes and a decrease in the mean and max surface distance from 0.75 ± 0.60mm and 8.63 ± 4.44mm to 0.30 ± 0.27mm and 3.65 ± 2.87mm, respectively.

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Yinong Wang, Jianhua Yao, Holger R. Roth, Joseph E. Burns, and Ronald M. Summers "Improving vertebra segmentation through joint vertebra-rib atlases", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 97853O (24 March 2016); https://doi.org/10.1117/12.2217118

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