从单张二维DXA片推断三维脊柱形状，提升侧弯诊断精度
3D Spine Shape Estimation from Single 2D DXA
- 通过预测脊柱矢状面轮廓，结合DXA冠状面信息重建3D形态
- 基于3万余对DXA与MRI配对数据训练，测试集表现优异
- 适用于脊柱侧弯量化分析，临床医生与影像研究者必看
脊柱侧弯传统上仅依赖二维侧向偏差评估，但近期研究揭示了其他成像平面在理解脊柱畸形中的重要性。因此，提取三维脊柱几何结构有助于量化这些变形并辅助诊断。本研究提出一种自动化通用框架，从二维DXA扫描中估计三维脊柱形状。方法通过显式预测DXA图像对应的脊柱矢状视图，结合DXA中的冠状视图，共同描述脊柱的三维形态。预测模型基于超过3万对DXA与MRI配对图像训练。在独立测试集上评估性能，结果表明方法具有高准确性。
原文摘要 · Abstract (English)
Scoliosis is traditionally assessed based solely on 2D lateral deviations, but recent studies have also revealed the importance of other imaging planes in understanding the deformation of the spine. Consequently, extracting the spinal geometry in 3D would help quantify these spinal deformations and aid diagnosis. In this study, we propose an automated general framework to estimate the 3D spine shape from 2D DXA scans. We achieve this by explicitly predicting the sagittal view of the spine from the DXA scan. Using these two orthogonal projections of the spine (coronal in DXA, and sagittal from the prediction), we are able to describe the 3D shape of the spine. The prediction is learnt from over 30k paired images of DXA and MRI scans. We assess the performance of the method on a held out test set, and achieve high accuracy.
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