Abstract
In this paper, we propose a new pipeline to perform accurate spinal curvature estimation. The framework, named as Seg4Reg, contains two deep neural networks focusing on segmentation and regression, respectively. Based on the results generated by the segmentation model, the regression network directly predicts the cobb angles from segmentation masks. To alleviate the domain shift problem appeared between training and testing sets, we also conduct a domain adaptation module into network structures. Finally, by ensembling the predictions of different models, our method achieves 21.71 SMAPE in the testing set.
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The first two authors contributed equally.
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Lin, Y., Zhou, HY., Ma, K., Yang, X., Zheng, Y. (2020). Seg4Reg Networks for Automated Spinal Curvature Estimation. In: Cai, Y., Wang, L., Audette, M., Zheng, G., Li, S. (eds) Computational Methods and Clinical Applications for Spine Imaging. CSI 2019. Lecture Notes in Computer Science(), vol 11963. Springer, Cham. https://doi.org/10.1007/978-3-030-39752-4_7
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DOI: https://doi.org/10.1007/978-3-030-39752-4_7
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