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Structure-Aware Sparse-View X-ray 3D Reconstruction
Feb. 20, 2024, 5:48 a.m. | Yuanhao Cai, Jiahao Wang, Zongwei Zhou, Angtian Wang, Alan Yuille
cs.CV updates on arXiv.org arxiv.org
Abstract: X-ray, known for its ability to reveal internal structures of objects, is expected to provide richer information for 3D reconstruction than visible light. Yet, existing neural radiance fields (NeRF) algorithms overlook this important nature of X-ray, leading to their limitations in capturing structural contents of imaged objects. In this paper, we propose a framework, Structure-Aware X-ray Neural Radiodensity Fields (SAX-NeRF), for sparse-view X-ray 3D reconstruction. Firstly, we design a Line Segment-based Transformer (Lineformer) as the …
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