Get Started
Home
Topics
Search
Library
Research questionHow can sparse-view CBCT reconstruction recover multiple tissue materials without manual bounds or hallucinated geometry?Sparse-view acquisition can reduce radiation exposure, but limited projections make attenuation and tissue boundaries ambiguous. The ambiguity becomes harder to resolve when scans contain several overlapping materials.
AI
Computer Vision
Health
Image & Video Processing
Research Paper
Technology
Latest papersRecent research connected to this question, newest first.$K$-NeAS: Scalable Multi-Material CT Reconstruction Using Neural SDFsThe source addresses neural signed-distance-field reconstruction for sparse-view clinical CBCT, including automated attenuation bounding and multi-material modeling. Evidence comes from four clinical CBCT datasets, with results reported for material counts up to three and 5- and 10-view settings; broader clinical deployment is not established.research paper · Sep 2, 2026
Related questions
How can surgical perception reconstruct 3D surfaces accurately from sparse endoscopic viewpoints?How can multi-view 3D reconstruction predict precise depth while preserving controllable uncertainty over plausible shapes?How can systems recover individually editable meshes for hundreds of objects from limited, heavily occluded views?How can sparse-view 3D scene representations avoid cross-view artifacts without costly per-scene reconstruction?