Perspective Projection-Based 3D CT Reconstruction from Biplanar X-rays
This addresses a medical imaging challenge for clinical applications by offering a lower-radiation alternative to traditional CT scans, though it appears incremental as it builds on existing reconstruction methods.
The paper tackles the problem of reconstructing 3D CT volumes from two perpendicular 2D X-ray images to reduce radiation exposure, proposing PerX2CT, which shows superior performance in multiple evaluation metrics compared to baselines.
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.