标题： Swin-X2S：使用Swin变换器从二维双平面X射线重建三维形状 显示英文标题

标题： Swin-X2S: Reconstructing 3D Shape from 2D Biplanar X-ray with Swin Transformers

摘要： 从二维X射线到三维形状的转换在提高诊断效率和安全性方面具有重要潜力。 然而，现有的重建方法通常依赖于手工设计的特征、人工干预和先验知识，导致形状误差不稳定并增加额外的处理成本。 在本文中，我们引入了Swin-X2S，这是一种端到端的深度学习方法，可直接从二维双平面正交X射线图像中重建三维分割和标记。 Swin-X2S采用编码器-解码器架构：编码器利用二维Swin Transformer进行X射线信息提取，而解码器则采用带有交叉注意力的三维卷积来整合来自正交视图的结构特征。 引入了一个维度扩展模块，以连接编码器和解码器，确保从二维像素到三维体素的平滑转换。 我们通过在涵盖四个解剖结构（股骨、髋关节、脊柱和肋骨）的九个公开数据集上进行广泛定性和定量实验来评估所提出的方法，总共有54个类别。 不仅在分割和标记指标方面，而且在实际应用中首要关注的临床相关参数方面，都观察到了对之前方法的显著改进，这证明了Swin-X2S在临床场景中提供有效解剖形状重建选项的前景。 代码实现可在以下位置获得：\url{https://github.com/liukuan5625/Swin-X2S} 显示英文摘要

摘要： The conversion from 2D X-ray to 3D shape holds significant potential for improving diagnostic efficiency and safety. However, existing reconstruction methods often rely on hand-crafted features, manual intervention, and prior knowledge, resulting in unstable shape errors and additional processing costs. In this paper, we introduce Swin-X2S, an end-to-end deep learning method for directly reconstructing 3D segmentation and labeling from 2D biplanar orthogonal X-ray images. Swin-X2S employs an encoder-decoder architecture: the encoder leverages 2D Swin Transformer for X-ray information extraction, while the decoder employs 3D convolution with cross-attention to integrate structural features from orthogonal views. A dimension-expanding module is introduced to bridge the encoder and decoder, ensuring a smooth conversion from 2D pixels to 3D voxels. We evaluate proposed method through extensive qualitative and quantitative experiments across nine publicly available datasets covering four anatomies (femur, hip, spine, and rib), with a total of 54 categories. Significant improvements over previous methods have been observed not only in the segmentation and labeling metrics but also in the clinically relevant parameters that are of primary concern in practical applications, which demonstrates the promise of Swin-X2S to provide an effective option for anatomical shape reconstruction in clinical scenarios. Code implementation is available at: \url{https://github.com/liukuan5625/Swin-X2S}.