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射线计算断层摄影(CT)是用于诊断医疗领域各种疾病的最常用的成像技术之一,其高对比敏感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,由于它涉及对病人和外科医生的潜在有害辐射照射,因此,从垂直的2DX射线图像中重建3D CT体积被认为是一个大有希望的替代办法,因为其辐射风险较低,而且更容易获得。然而,这非常具有挑战性,因为它需要从2D图象中重建3D解剖学信息,其观点有限,所有信息都重叠。在本文件中,我们提议采用PerX2CT,这是X光新颖的CT重建框架,反映视角预测计划。我们提议的方法为每个坐标提供了不同的特征组合,使模型能够隐含地获得关于3D位置的信息。我们揭示了通过正确使用协调的本地和全球特征来正确重建选定部分高分辨率的潜力。我们的方法表明,有可能在低计算复杂性和快速推断时间的临床应用中,在多度基准中显示性优于性。</s>