arXiv subjects

Jingcheng Yuan

Publications and source records attributed to Jingcheng Yuan.

3 recordsLinked to original sources

arXiv2026

Effects of Quantum Noise and Source Blurring on Dark-Field Signal Retrieval in X-ray Speckle-Based Imaging

X-ray speckle-based dark-field imaging offers high sensitivity to sub-pixel structural features, yet its quantitative reliability in clinical and preclinical settings remains constrained by low photon flux and finite focal spot sizes. However, how hardware-induced noise and source blurring propagate through retrieval algorithms to degrade signal integrity is not fully understood. Here, we systematically evaluate algorithm robustness quantified by signal linearity, sensitivity, and bias under photon starvation and source blurring across two mathematically distinct frameworks: differential-based intrinsic tracking (Low-Coherence System, LCS) and patch-wise explicit tracking (X-ray Speckle-Tracking Speckle-Vector-Tracking, XST-XSVT). Our experimental results demonstrate that input speckle pattern distortions propagate through retrieval algorithms in fundamentally different ways depending on algorithm architecture. As an example, using our setup, under severe photon starvation, derivative noise amplification in LCS causes its dark-field signal linearity and sensitivity to drop precipitously, while sharply elevating baseline bias. In contrast, XST-XSVT restricts these losses for sensitivity while maintaining a stable baseline, as its patch-wise variance calculation inherently suppresses stochastic noise. Similarly, under blur-limited conditions , source blurring washes out the speckle pattern, directly reducing dark-field sensitivity for both LCS and XST-XSVT. This characterization establishes operational boundaries for low-power and low-coherence X-ray systems, guiding algorithm selection and framework optimization to realize quantitative dark-field imaging in preclinical and clinical applications.

physics.optics↗

arXiv2025

Single-Shot, Single-Mask X-ray Dark-field and Phase Contrast Imaging

X-ray imaging, traditionally relying on attenuation contrast, struggles to differentiate materials with similar attenuation coefficients like soft tissues. X-ray phase contrast imaging (XPCI) and dark-field (DF) imaging provide enhanced contrast by detecting phase shifts and ultra-small-angle X-ray scattering (USAXS). However, they typically require complex and costly setups, along with multiple exposures to retrieve various contrast features. In this study, we introduce a novel single-mask X-ray imaging system design that simultaneously captures attenuation, differential phase contrast (DPC), and dark-field images in a single exposure. Most importantly, our proposed system design requires just a single mask alignment with relatively low-resolution detectors. Using our novel light transport models derived for these specific system designs, we show intuitive understanding of contrast formation and retrieval method of different contrast features. Our approach eliminates the need for highly coherent X-ray sources, ultra-high-resolution detectors, spectral detectors or intricate gratings. We propose three variations of the single-mask setup, each optimized for different contrast types, offering flexibility and efficiency in a variety of applications. The versatility of this single-mask approach along with the use of befitting light transport models holds promise for broader use in clinical diagnostics and industrial inspection, making advanced X-ray imaging more accessible and cost-effective.

physics.med-ph↗

arXiv2024

Transport-of-Intensity Model for Single-Mask X-ray Differential Phase Contrast Imaging

X-ray phase contrast imaging holds great promise for improving the visibility of light-element materials such as soft tissues and tumors. Single-mask differential phase contrastnimaging method stands out as a simple and effective approach to yield differential phase contrast. In this work, we introduce a novel model for a single-mask phase imaging system based on the transport-of-intensity equation. Our model provides an accessible understanding of signal and contrast formation in single-mask X-ray phase imaging, offering a clear perspective on the image formation process, for example, the origin of alternate bright and dark fringes in phase contrast intensity images. Aided by our model, we present an efficient retrieval method that yields differential phase contrast imagery in a single acquisition step. Our model gives insight into the contrast generation and its dependence on the system geometry and imaging parameters in both the initial intensity image as well as in retrieved images. The model validity as well as the proposed retrieval method is demonstrated via both experimental results on a system developed in-house as well as with Monte Carlo simulations. In conclusion, our work not only provides a model for an intuitive visualization of image formation but also offers a method to optimize differential phase imaging setups, holding tremendous promise for advancing medical diagnostics and other applications.

eess.IV↗