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The Impact of Loss Functions and Scene Representations for 3D/2D Registration on Single-view Fluoroscopic X-ray Pose Estimation
Feb. 28, 2024, 5:44 a.m. | Chaochao Zhou, Syed Hasib Akhter Faruqui, Abhinav Patel, Ramez N. Abdalla, Michael C. Hurley, Ali Shaibani, Matthew B. Potts, Babak S. Jahromi, Sameer
cs.LG updates on arXiv.org arxiv.org
Abstract: Many tasks performed in image-guided procedures can be cast as pose estimation problems, where specific projections are chosen to reach a target in 3D space. In this study, we first develop a differentiable projection (DiffProj) rendering framework for the efficient computation of Digitally Reconstructed Radiographs (DRRs) with automatic differentiability from either Cone-Beam Computerized Tomography (CBCT) or neural scene representations, including two newly proposed methods, Neural Tuned Tomography (NeTT) and masked Neural Radiance Fields (mNeRF). We …
abstract arxiv cs.cv cs.lg differentiable eess.iv framework functions image impact loss projection ray registration rendering space study tasks type view x-ray
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The Perception-Robustness Tradeoff in Deterministic Image Restoration
1 day, 21 hours ago |
arxiv.org
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