arXiv (All)
open access
Bayesian Joint Reconstruction and Uncertainty Quantification for Limited-Data Multi-Contrast X-Ray CT
Multi-contrast X-ray computed tomography (CT) combines attenuation contrast with phase and dark-field contrast, which are sensitive to refraction and ultra-small-angle scattering, respectively. Common implementations record several intensity measurements per projection angle by phase or mask steppin
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Comparing image quality of synchrotron and laboratory nano-CT scans: a round robin study#1266120
- Cross-Domain TransNet for sparse-view CT reconstruction.#392851
- Denoising framework for X-ray absorption spectroscopy data.#159812
- Efficient Bayesian inference for learning in the Ising linear perceptron and signal detection in CDMA#230082
- Improved in-plane visibility of tumors using breast tomosynthesis#823224
Record · ID 1356742
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive