A subspace-based resolution-enhancing image reconstruction method for few-view differential phase-contrast tomography

It is well known that properly designed image reconstruction methods can facilitate reductions in imaging doses and data-acquisition times in tomographic imaging. The ability to do so is particularly important for emerging modalities, such as differential x-ray phase-contrast tomography (D-XPCT), which are currently limited by these factors. An important application of D-XPCT is high-resolution imaging of biomedical samples. However, reconstructing high-resolution images from few-view tomographic measurements remains a challenging task due to the high-frequency information loss caused by data incompleteness. In this work, a subspace-based reconstruction strategy is proposed and investigated for use in few-view D-XPCT image reconstruction. By adopting a two-step approach, the proposed method can simultaneously recover high-frequency details within a certain region of interest while suppressing noise and/or artifacts globally. The proposed method is investigated by the use of few-view experimental data acquired by an edge-illumination D-XPCT scanner

A joint-reconstruction approach for single-shot edge illumination x-ray phase-contrast tomography

Edge illumination X-ray phase-contrast tomography (EIXPCT) is an imaging technique that estimates the spatially variant X-ray refractive index and absorption distribution within an object while seeking to circumvent the limitations of previous benchtop implementations of X-ray phase-contrast tomography. As with gratingor analyzer-based methods, conventional image reconstruction methods for EIXPCT require that two or more images be acquired at each tomographic view angle. This requirement leads to increased data acquisition times, hindering in vivo applications. To circumvent these limitations, a joint reconstruction (JR) approach is proposed that concurrently produces estimates of the refractive index and absorption distributions from a tomographic data set containing only a single image per tomographic view angle. The JR reconstruction method solves a nonlinear optimization problem by use of a novel iterative gradient-based algorithm. The JR method is demonstrated in both computer-simulated and experimental EIXPCT studies

Comparison of data-acquisition designs for single-shot edge-illumination X-ray phase-contrast tomography

Edge-illumination X-ray phase-contrast tomography (EIXPCT) is an emerging technique that enables practical phase-contrast imaging with laboratory-based X-ray sources. A joint reconstruction method was proposed for reconstructing EIXPCT images, enabling novel flexible data-acquisition designs. However, only limited efforts have been devoted to optimizing data-acquisition designs for use with the joint reconstruction method. In this study, several promising designs are introduced, such as the constant aperture position (CAP) strategy and the alternating aperture position (AAP) strategy covering different angular ranges. In computer-simulation studies, these designs are analyzed and compared. Experimental data are employed to test the designs in real-world applications. All candidate designs are also compared for their implementation complexity. The tradeoff between data-acquisition time and image quality is discussed

The stochastic digital human is now enrolling for in silico imaging trials -- Methods and tools for generating digital cohorts

Randomized clinical trials, while often viewed as the highest evidentiary bar by which to judge the quality of a medical intervention, are far from perfect. In silico imaging trials are computational studies that seek to ascertain the performance of a medical device by collecting this information entirely via computer simulations. The benefits of in silico trials for evaluating new technology include significant resource and time savings, minimization of subject risk, the ability to study devices that are not achievable in the physical world, allow for the rapid and effective investigation of new technologies and ensure representation from all relevant subgroups. To conduct in silico trials, digital representations of humans are needed. We review the latest developments in methods and tools for obtaining digital humans for in silico imaging studies. First, we introduce terminology and a classification of digital human models. Second, we survey available methodologies for generating digital humans with healthy and diseased status and examine briefly the role of augmentation methods. Finally, we discuss the trade-offs of four approaches for sampling digital cohorts and the associated potential for study bias with selecting specific patient distributions

Single-shot edge illumination x-ray phase-contrast tomography enabled by joint image reconstruction

Edge illumination x-ray phase-contrast tomography (EIXPCT) is an emerging x-ray phase-contrast tomography technique for reconstructing the complex-valued x-ray refractive index distribution of an object. Conventional image reconstruction approaches for EIXPCT require multiple images to be acquired at each tomographic view angle. This contributes to prolonged data-acquisition times and elevated radiation doses, which can hinder in vivo applications. In this work, a new “single-shot” method is proposed for joint reconstruction (JR) of the real and imaginaryvalued components of the refractive index distribution from a tomographic data set that contains only a single image acquired at each view angle. The proposed method is predicated on a nonlinear formulation of the inverse problem that is solved by using a gradient-based optimization method. The method is validated and investigated using computersimulated and experimental EIXPCT data sets

Predicting photooxidant concentrations in aerosol liquid water based on laboratory extracts of ambient particles

Aerosol liquid water (ALW) is a unique reaction medium, but its chemistry is poorly understood. For example, little is known of photooxidant concentrations – including hydroxyl radicals (⚫OH), singlet molecular oxygen (1O2*), and oxidizing triplet excited states of organic matter (3C*) – even though they likely drive much of ALW chemistry. Due to the very limited water content of particles, it is difficult to quantify oxidant concentrations in ALW directly. To predict these values, we measured photooxidant concentrations in illuminated aqueous particle extracts as a function of dilution and used the resulting oxidant kinetics to extrapolate to ALW conditions. We prepared dilution series from two sets of particles collected in Davis, California: one from winter (WIN) and one from summer (SUM). Both periods are influenced by biomass burning, with dissolved organic carbon (DOC) in the extracts ranging from 10 to 495 mg C  L−1. In the winter sample, the ⚫OH concentration is independent of particle mass concentration, with an average value of 5.0 (± 2.2) × 10−15 M, while in summer ⚫OH increases with DOC in the range (0.4–7.7) × 10−15 M. In both winter and summer samples, 3C* concentrations increase rapidly with particle mass concentrations in the extracts and then plateau under more concentrated conditions, with a range of (0.2–7) × 10−13 M. WIN and SUM have the same range of 1O2* concentrations, (0.2–8.5) × 10−12 M, but in WIN the 1O2* concentration increases linearly with DOC, while in SUM 1O2* approaches a plateau. We next extrapolated the relationships of oxidant formation rates and sinks as a function of particle mass concentration from our dilute extracts to the much more concentrated condition of aerosol liquid water. Predicted ⚫OH concentrations in ALW (including mass transport of ⚫OH from the gas phase) are (5–8) × 10−15 M, similar to those in fog/cloud waters. In contrast, predicted concentrations of 3C* and 1O2* in ALW are approximately 10 to 100 times higher than in cloud/fogs, with values of (4–9) × 10−13 M and (1–5) × 10−12 M, respectively. Although ⚫OH is often considered the main sink for organic compounds in the atmospheric aqueous phase, the much higher concentrations of 3C* and 1O2* in aerosol liquid water suggest these photooxidants will be more important sinks for many organics in particle water.</p