Retinex-qDPC: Automatic background-rectified quantitative differential phase contrast imaging.

BACKGROUND AND OBJECTIVE: The quality of quantitative differential phase contrast reconstruction (qDPC) can be severely degenerated by the mismatch of the background of two oblique illuminated images, yielding problematic phase recovery results. These background mismatches may result from illumination patterns, inhomogeneous media distribution, or other defocusing layers. In previous reports, the background is manually calibrated which is time-consuming, and unstable, since new calibrations are needed if any modification to the optical system was made. It is also impossible to calibrate the background from the defocusing layers, or for high dynamic observation as the background changes over time. The background mismatch reduces the experimental robustness of qDPC and largely limits its applications. To tackle the mismatch of background and increases the experimental robustness, we propose the Retinex-qDPC. METHODS: In Retinex-qDPC, we replace the data fidelity term of the previous cost function for qDPC inverse problem, by the images' edge features yielding L2-Retinex-qDPC and L1-Retinex-qDPC for high background-robustness qDPC reconstruction. The split Bregman method is used to solve the L1-Retinex DPC. We compare both Retinex-qDPC models against state-of-the-art DPC reconstruction algorithms including total-variation regularized qDPC, and isotropic-qDPC using both simulated and experimental data. RESULTS: Retinex qDPC can significantly improve the phase recovery quality by suppressing the impact of mismatch background. Within, the L1-Retinex-qDPC is better than L2-Retinex and other state-of-the-art qDPC algorithms. CONCLUSIONS: The Retinex-qDPC increases the experimental robustness against background illumination without any modification of the optical system, which will benefit all qDPC applications.

Direct information retrieval after 3D reconstruction in grating-based X-ray phase-contrast computed tomography.

Grating-based X-ray differential phase-contrast imaging has attracted a great amount of attention and has been considered as a potential imaging method in clinical medicine because of its compatibility with the traditional X-ray tube source and the possibility of a large field of view. Moreover, phase-contrast computed tomography provides three-dimensional phase-contrast visualization. Generally, two-dimensional information retrieval performed on every projection is required prior to three-dimensional reconstruction in phase-contrast computed tomography. In this paper, a three-dimensional information retrieval method to separate absorption and phase information directly from two reconstructed images is derived. Theoretical derivations together with numerical simulations have been performed to confirm the feasibility and veracity of the proposed method. The advantages and limitations compared with the reverse projection method are also discussed. Owing to the reduced data size and the absence of a logarithm operation, the computational time for information retrieval is shortened by the proposed method. In addition, the hybrid three-dimensional images of absorption and phase information were reconstructed using an absorption reconstruction algorithm, hence the existing data pre-processing methods and iterative reconstruction algorithms in absorption reconstruction may be utilized in phase reconstruction immediately.

Hard X-ray index of refraction tomography of a whole rabbit knee joint: A feasibility study.

We report results of the computed tomography reconstruction of the index of refraction in a whole rabbit knee joint examined at the photon energy of 51keV. Refraction based images make it possible to delineate the bone, cartilage, and soft tissues without adjusting the contrast window width and level. Density variations, which are related to tissue composition and are not visible in absorption X-ray images, are detected in the obtained refraction based images. We discuss why refraction-based images provide better detectability of low contrast features than absorption images.

Interior Tomography from Differential Phase Contrast Data via Hilbert Transform Based on Spline Functions.

X-ray phase contrast imaging is an important mode due to its sensitivity to subtle features of soft biological tissues. Grating-based differential phase contrast (DPC) imaging is one of the most promising phase imaging techniques because it works with a normal x-ray tube of a large focal spot at a high flux rate. However, a main obstacle before this paradigm shift is the fabrication of large-area gratings of a small period and a high aspect ratio. Imaging large objects with a size-limited grating results in data truncation which is a new type of the interior problem. While the interior problem was solved for conventional x-ray CT through analytic extension, compressed sensing and iterative reconstruction, the difficulty for interior reconstruction from DPC data lies in that the implementation of the system matrix requires the differential operation on the detector array, which is often inaccurate and unstable in the case of noisy data. Here, we propose an iterative method based on spline functions. The differential data are first back-projected to the image space. Then, a system matrix is calculated whose components are the Hilbert transforms of the spline bases. The system matrix takes the whole image as an input and outputs the back-projected interior data. Prior information normally assumed for compressed sensing is enforced to iteratively solve this inverse problem. Our results demonstrate that the proposed algorithm can successfully reconstruct an interior region of interest (ROI) from the differential phase data through the ROI.

Clinical boundary conditions for grating-based differential phase-contrast mammography.

Research in grating-based differential phase-contrast imaging (DPCI) has gained increasing momentum in the past couple of years. The first results on the potential clinical benefits of the technique for X-ray mammography are becoming available and indicate improvements in terms of general image quality, the delineation of lesions versus the background tissue and the visibility of microcalcifications. In this paper, we investigate some aspects related to the technical feasibility of DPCI for human X-ray mammography. After a short introduction to state-of-the-art full-field digital mammography in terms of technical aspects as well as clinical aspects, we put together boundary conditions for DPCI. We then discuss the implications for system design in a comparative manner for systems with two-dimensional detectors versus slit-scanning systems, stating advantages and disadvantages of the two designs. Finally, focusing on a slit-scanning system, we outline a possible concept for phase acquisition.

Single-slice reconstruction method for helical cone-beam differential phase-contrast CT.

X-ray phase-contrast computed tomography (PC-CT) can provide the internal structure information of biomedical specimens with high-quality cross-section images and has become an invaluable analysis tool. Here a simple and fast reconstruction algorithm is reported for helical cone-beam differential PC-CT (DPC-CT), which is called the DPC-CB-SSRB algorithm. It combines the existing CB-SSRB method of helical cone-beam absorption-contrast CT with the differential nature of DPC imaging. The reconstruction can be performed using 2D fan-beam filtered back projection algorithm with the Hilbert imaginary filter. The quality of the results for large helical pitches is surprisingly good. In particular, with this algorithm comparable quality is obtained using helical cone-beam DPC-CT data with a normalized pitch of 10 to that obtained using the traditional inter-row interpolation reconstruction with a normalized pitch of 2. This method will push the future medical helical cone-beam DPC-CT imaging applications.

An algebraic iterative reconstruction technique for differential X-ray phase-contrast computed tomography.

Iterative reconstruction has a wide spectrum of proven advantages in the field of conventional X-ray absorption-based computed tomography (CT). In this paper, we report on an algebraic iterative reconstruction technique for grating-based differential phase-contrast CT (DPC-CT). Due to the differential nature of DPC-CT projections, a differential operator and a smoothing operator are added to the iterative reconstruction, compared to the one commonly used for absorption-based CT data. This work comprises a numerical study of the algorithm and its experimental verification using a dataset measured at a two-grating interferometer setup. Since the algorithm is easy to implement and allows for the extension to various regularization possibilities, we expect a significant impact of the method for improving future medical and industrial DPC-CT applications.