X-ray computed tomography (CT) is one of the most common imaging techniques used to diagnose various diseases in the medical field. Its high contrast sensitivity and spatial resolution allow the physician to observe details of body parts such as bones, soft tissue, blood vessels, etc. As it involves potentially harmful radiation exposure to patients and surgeons, however, reconstructing 3D CT volume from perpendicular 2D X-ray images is considered a promising alternative, thanks to its lower radiation risk and better accessibility. This is highly challenging though, since it requires reconstruction of 3D anatomical information from 2D images with limited views, where all the information is overlapped. In this paper, we propose PerX2CT, a novel CT reconstruction framework from X-ray that reflects the perspective projection scheme. Our proposed method provides a different combination of features for each coordinate which implicitly allows the model to obtain information about the 3D location. We reveal the potential to reconstruct the selected part of CT with high resolution by properly using the coordinate-wise local and global features. Our approach shows potential for use in clinical applications with low computational complexity and fast inference time, demonstrating superior performance than baselines in multiple evaluation metrics.

翻译：X射线计算机断层扫描（CT）是医学领域用于诊断多种疾病最常用的成像技术之一。其高对比度灵敏度和空间分辨率使医生能够观察骨骼、软组织、血管等身体部位的细节。然而，由于该技术涉及对患者和外科医生的潜在有害辐射暴露，从垂直方向的二维X射线图像重建三维CT体积被认为是一种有前景的替代方案，因其辐射风险较低且可及性更好。尽管如此，这一任务极具挑战性，因为它需要从有限视角的二维图像中重建三维解剖信息，而所有信息均相互重叠。本文提出了PerX2CT，一种新颖的基于X射线的CT重建框架，该框架反映了透视投影方案。我们的方法为每个坐标提供不同的特征组合，从而隐式地使模型能够获取三维位置信息。通过合理利用坐标层面的局部和全局特征，我们揭示了以高分辨率重建选定CT部分的潜力。我们的方法在低计算复杂度和快速推理时间方面展现出临床应用的潜力，并在多项评估指标上优于基线方法。