In-line x-ray phase-contrast (XPC) tomosynthesis combines the concepts of tomosynthesis and in-line XPC imaging to utilize the advantages of both for biological imaging applications. Tomosynthesis permits reductions in acquisition times compared with conventional tomography scans while in-line XPC imaging provides high contrast and resolution in images of weakly absorbing materials. In this work, we develop an advanced iterative algorithm as an approach for dealing with the incomplete (and often noisy) data inherent to XPC tomosynthesis. We also investigate the depth resolution properties of XPC tomosynthesis and demonstrate that the <i>z</i>-resolution properties of XPC tomosynthesis is superior to that of conventional absorption-based tomosynthesis. More specifically, we find in-plane structures display strong boundary-enhancement while out-of-plane structures do not. This effect can facilitate the identification of in-plane structures.
In this work, we report on the development of an advanced multi-channel (MC) image reconstruction algorithm for grating-based X-ray phase-contrast computed tomography (GB-XPCT). The MC reconstruction method we have developed operates by concurrently, rather than independently as is done conventionally, reconstructing tomographic images of the three object properties (absorption, small-angle scattering, refractive index). By jointly estimating the object properties by use of an appropriately defined penalized weighted least squares (PWLS) estimator, the 2nd order statistical properties of the object property sinograms, including correlations between them, can be fully exploited to improve the variance vs. resolution tradeoff of the reconstructed images as compared to existing methods. Channel-independent regularization strategies are proposed. To solve the MC reconstruction problem, we developed an advanced algorithm based on the proximal point algorithm and the augmented Lagrangian method. By use of experimental and computer-simulation data, we demonstrate that by exploiting inter-channel noise correlations, the MC reconstruction method can improve image quality in GB-XPCT.
It has been proposed that the sensitivity of breast lesion detection can be improved with phase-contrast mammographic
imaging. The recently introduced clinical system by Konica-Minolta, for example, reportedly yields enhanced lesion
detectability. We hypothesize that the use of an optimized x-ray spectrum will result in even better performance. To test
this hypothesis, we have performed a study of several clinical spectra from Mo and W sources over a broad spectral
range. In the study, we have incorporated established dose measurements from a simple breast phantom used in the
digital mammography literature, which has been updated to incorporate breast density properties in addition to
conventional attenuation information. Established phase-contrast imaging simulation techniques, which employed a
Fresnel propagator, were used to generate edge-enhanced radiographs for analysis. In addition, detector sensitivity and
tube loading parameters were incorporated into the analysis. The resulting mammography images were analyzed via
measurement of object edge-enhanced contrast.
Intensity diffraction tomography (I-DT) is a non-interferometric imaging method for reconstructing the complex-valued
refractive index distribution of a weakly scattering object. The original formulation of I-DT requires
measurement of two in-line intensity measurements on parallel detector planes at each tomographic view angle.
In this work, a reconstruction theory for multi-spectral is established and investigated for use with single material
objects whose dispersion characteristics are known a priori. Unlike other I-DT methods, the temporal frequency
of the illuminating plane-wave represents the degree-of-freedom of the imaging system that is varied to acquire
two independent intensity measurements on a fixed detector-plane. Moreover, the proposed method accounts for