The paper introduces LiftXR, a geometry‑guided framework that first reconstructs a 3D anatomical layout from bi‑planar X‑ray images and then uses this layout to guide CT volume reconstruction. An anatomical parser refines the layout by analyzing the reconstructed CT, enabling region‑specific intensity calibration. Experiments on two public datasets show LiftXR surpasses recent X‑ray‑to‑CT methods and improves downstream segmentation performance.
By Yifei Wu, Yicheng Wu, Qiang Ma, Qi Chen, Renyang Gu, Xinyu Liu, Yongsheng Pan, Yong Xia
Generating a 3D dental volume from a single panoramic radiograph (PXR) could provide a low-radiation alternative to Cone-Beam Computed Tomography (CBCT), but the problem is highly underdetermined: panoramic acquisition integrates 3D attenuation along curved X-ray paths into a 2D image, leaving depth-resolved anatomy unobserved. Existing implicit and generative approaches often produce oversmoothed geometry or anatomically inconsistent hallucinations, lacking geometry-driven supervision and relying on smooth representations unable to precisely localize sharp anatomical boundaries.
arXiv:2603.26509v2 Announce Type: replace
Abstract: Computed tomography (CT) provides rich 3D anatomical detail but is often constrained by high radiation exposure, substantial costs, and limited ava...
By Martin Rath, Morteza Ghahremani, Yitong Li, Ashkan Taghipour, Marcus Makowski, Christian Wachinger
arXiv:2609.37605v1 Announce Type: cross
Abstract: Supervised deep learning has advanced sparse-view tomographic reconstruction. However, conventional models, which typically map filtered back-project...
By AmirEhsan Khorashadizadeh, Benjam\'in B\'ejar
arXiv:2505. 17338v3 Announce Type: replace-cross Abstract: Photorealistic volumetric rendering of CT scans greatly benefits clinical workflows, yet neural approaches such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) require prohibitive per-scan optimization (hours for NeRF, about 30 minutes for 3DGS), making them impractical in clinical settings.
By Zhongpai Gao, Benjamin Planche, Meng Zheng, Anwesa Choudhuri, Van Nguyen Nguyen, Terrence Chen, Ziyan Wu
arXiv:2607. 23343v1 Announce Type: cross Abstract: Intraoperative 2D/3D registration aligns preoperative CT volumes with intraoperative X-ray or fluoroscopic images and is essential for image-guided interventions.
By Minheng Chen, Youyong Kong