Directional dark-field retrieval with single-grid x-ray imaging
Directional dark-field imaging is an emerging x-ray modality that is sensitive to unresolved anisotropic scattering from sub-pixel sample microstructures. A single-grid imaging set-up can be used to capture dark-field images by looking at changes in a grid pattern projected upon the sample. By creating analytical models for the experiment, we have developed a single-grid directional dark field retrieval algorithm that can extract dark-field parameters such as the dominant scattering direction, and the semi-major and -minor scattering angles. We show that this method is effective even in the presence of high image noise, allowing for low dose and time sequence imaging.
Code (1)
Tasks
RetrievalSimilar Papers 제목 키워드 기반
Dark-field and directional dark-field on low coherence X-ray sources with random mask modulations: validation with SAXS anisotropy measurements
Phase Contrast Imaging (PCI), Dark-Field (DF) and Directional Dark-Field (DDF) imaging are recent X-ray imaging modalities that have demonstrated their interest by providing access to information and contrasts different …
Probabilistic reconstruction of Dark Matter fields from biased tracers using diffusion models
Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter components that cannot be directly observed. The relationship between dark matter density fields and galaxy distributions can be…
Efficient phase retrieval based on dark fringe recognition with an ability of bypassing invalid fringes
This paper discusses the noisy phase retrieval problem: recovering a complex image signal with independent noise from quadratic measurements. Inspired by the dark fringes shown in the measured images of the array detecto…
RetrievalFast emulation of cosmological density fields based on dimensionality reduction and supervised machine-learning
N-body simulations are the most powerful method to study the non-linear evolution of large-scale structure. However, they require large amounts of computational resources, making unfeasible their direct adoption in scena…
CPUDimensionality ReductionSingle View Refractive Index Tomography with Neural Fields
Refractive Index Tomography is the inverse problem of reconstructing the continuously-varying 3D refractive index in a scene using 2D projected image measurements. Although a purely refractive field is not directly visib…
3D Reconstruction