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Erschienen in:
2020 | OriginalPaper | Buchkapitel
Spinal Curve Guide Network (SCG-Net) for Accurate Automated Spinal Curvature Estimation
verfasst von : Shuxin Wang, Shaohui Huang, Liansheng Wang
Erschienen in: Computational Methods and Clinical Applications for Spine Imaging
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Abstract
Cobb angle plays an important role in the diagnosis of scoliosis, which can effectively quantify the degree of scoliosis. Manual measurement of Cobb angles is time-consuming, and the results are also heavily affected by the expert’s choice. In this paper, we propose a spine curve guide framework to directly regress the cobb angle from single AP view X-rays images. We firstly design a segmentation network to accurately segment two spine boundary, and then aggregate the obtained boundary scoremap with the original spinal X-rays images to input another angle estimation network to make high-precision regression prediction for cobb angle. We evaluate our method in the AASCE19 challenge, and our result achieves 22.1775 SMAPE that shows strong competitiveness compared to other excellent methods.