Numerical comparison of X-ray differential phase contrast and attenuation contrast

Image quality and scan time optimisation for in situ phase contrast x-ray tomography of the intervertebral disc

In-line phase contrast synchrotron tomography combined with in situ mechanical loading enables the characterisation of soft tissue micromechanics via digital volume correlation (DVC) within whole organs. Optimising scan time is important for reducing radiation dose from multiple scans and to limit sample movement during acquisition. Also, although contrasted edges provided by in-line phase contrast tomography of soft tissues are useful for DVC, the effect of phase contrast imaging on its accuracy has yet to be investigated. Due to limited time at synchrotron facilities, scan parameters are often decided during imaging and their effect on DVC accuracy is not fully understood. Here, we used previously published data of intervertebral disc phase contrast tomography to evaluate the influence of i) fibrous image texture, ii) number of projections, iii) tomographic reconstruction method, and iv) phase contrast propagation distance on DVC results. A greater understanding of how image texture influences optimal DVC tracking was obtained by visualising objective function mapping, enabling tracking inaccuracies to be identified. When reducing the number of projections, DVC was minimally affected by image high frequency noise but with a compromise in accuracy. Iterative reconstruction methods improved image signal-to-noise and consequently significantly lowered DVC displacement uncertainty. Propagation distance was shown to affect DVC accuracy. Consistent DVC results were achieved within a propagation distance range which provided contrast to the smallest scale features, where; too short a distance provided insufficient features to track, whereas too long led to edge effect inconsistencies, particularly at greater deformations. Although limited to a single sample type and image setup, this study provides general guidelines for future investigations when optimising image quality and scan times for in situ phase contrast x-ray tomography of fibrous connective tissues.

Acquisition of a single grid-based phase-contrast X-ray image using instantaneous frequency and noise filtering

BACKGROUND

To obtain phase-contrast X-ray images, single-grid imaging systems are effective, but Moire artifacts remain a significant issue. The solution for removing Moire artifacts from an image is grid rotation, which can distinguish between these artifacts and sample information within the Fourier space. However, the mechanical movement of grid rotation is slower than the real-time change in Moire artifacts. Thus, Moire artifacts generated during real-time imaging cannot be removed using grid rotation. To overcome this problem, we propose an effective method to obtain phase-contrast X-ray images using instantaneous frequency and noise filtering.

RESULT

The proposed phase-contrast X-ray image using instantaneous frequency and noise filtering effectively suppressed noise with Moire patterns. The proposed method also preserved the clear edge of the inner and outer boundaries and internal anatomical information from the biological sample, outperforming conventional Fourier analysis-based methods, including absorption, scattering, and phase-contrast X-ray images. In particular, when comparing the phase information for the proposed method with the x-axis gradient image from the absorption image, the proposed method correctly distinguished two different types of soft tissue and the detailed information, while the latter method did not.

CONCLUSION

This study successfully achieved a significant improvement in image quality for phase-contrast X-ray images using instantaneous frequency and noise filtering. This study can provide a foundation for real-time bio-imaging research using three-dimensional computed tomography.

Reweighted L1-norm regularized phase retrieval for x-ray differential phase contrast radiograph

Talbot-Lau x-ray grating interferometry greatly decreases the requirements on x-ray sources to realize differential phase contrast imaging and has found many applications in industrial and medical imaging. Phase retrieval from the noisy differential signal is crucial for quantitative analysis, comparison, and fusion with other imaging modalities. In this paper, we introduce a reweighted L1-norm based nonlinear regularization method for the phase retrieval problem. Both simulation and experimental results demonstrated that, comparing with the widely used L1-norm based regularization method and Wiener filter method, the proposed method is more effective both in eliminating the strip noises and in preserving the image detail.

Statistical iterative reconstruction algorithm for X-ray phase-contrast CT

Grating-based phase-contrast computed tomography (PCCT) is a promising imaging tool on the horizon for pre-clinical and clinical applications. Until now PCCT has been plagued by strong artifacts when dense materials like bones are present. In this paper, we present a new statistical iterative reconstruction algorithm which overcomes this limitation. It makes use of the fact that an X-ray interferometer provides a conventional absorption as well as a dark-field signal in addition to the phase-contrast signal. The method is based on a statistical iterative reconstruction algorithm utilizing maximum-a-posteriori principles and integrating the statistical properties of the raw data as well as information of dense objects gained from the absorption signal. Reconstruction of a pre-clinical mouse scan illustrates that artifacts caused by bones are significantly reduced and image quality is improved when employing our approach. Especially small structures, which are usually lost because of streaks, are recovered in our results. In comparison with the current state-of-the-art algorithms our approach provides significantly improved image quality with respect to quantitative and qualitative results. In summary, we expect that our new statistical iterative reconstruction method to increase the general usability of PCCT imaging for medical diagnosis apart from applications focused solely on soft tissue visualization.

Regularized iterative integration combined with non-linear diffusion filtering for phase-contrast x-ray computed tomography

Phase-contrast x-ray computed tomography has a high potential to become clinically implemented because of its complementarity to conventional absorption-contrast.In this study, we investigate noise-reducing but resolution-preserving analytical reconstruction methods to improve differential phase-contrast imaging. We apply the non-linear Perona-Malik filter on phase-contrast data prior or post filtered backprojected reconstruction. Secondly, the Hilbert kernel is replaced by regularized iterative integration followed by ramp filtered backprojection as used for absorption-contrast imaging. Combining the Perona-Malik filter with this integration algorithm allows to successfully reveal relevant sample features, quantitatively confirmed by significantly increased structural similarity indices and contrast-to-noise ratios. With this concept, phase-contrast imaging can be performed at considerably lower dose.

Comparison of two x-ray phase-contrast imaging methods with a microfocus source

We present a comparison for high-resolution imaging with a laboratory source between grating-based (GBI) and propagation-based (PBI) x-ray phase-contrast imaging. The comparison is done through simulations and experiments using a liquid-metal-jet x-ray microfocus source. Radiation doses required for detection in projection images are simulated as a function of the diameter of a cylindrical sample. Using monochromatic radiation, simulations show a lower dose requirement for PBI for small object features and a lower dose for GBI for larger object features. Using polychromatic radiation, such as that from a laboratory microfocus source, experiments and simulations show a lower dose requirement for PBI for a large range of feature sizes. Tested on a biological sample, GBI shows higher noise levels than PBI, but its advantage of quantitative refractive index reconstruction for multi-material samples becomes apparent.

Comparison of contrast-to-noise ratios of transmission and dark-field signal in grating-based X-ray imaging for healthy murine lung tissue

PURPOSE

An experimental comparison of the contrast-to-noise ratio (CNR) between transmission and dark-field signals in grating-based X-ray imaging for ex-vivo murine lung tissue.

MATERIALS AND METHODS

Lungs from three healthy mice were imaged ex vivo using a laser-driven compact synchrotron X-ray source. Background noise of transmission and dark-field signal was quantified by measuring the standard deviation in a region of interest (ROI) placed in a homogeneous area outside the specimen. Image contrast was quantified by measuring the signal range in rectangular ROIs placed in central and peripheral lung parenchyma. The relative contrast gain (RCG) of dark-field over transmission images was calculated as CNRDF / CNRT.

RESULTS

In all images, there was a trend for contrast-to-noise ratios of dark-field images (CNRDF) to be higher than for transmission images (CNRT) for all ROIs (median 61 vs. 38, p=0.10), but the difference was statistically significant only for peripheral ROIs (61 vs. 32, p=0.03). Median RCG was >1 for all ROIs (1.84). RCG values were significantly smaller for central ROIs than for peripheral ROIs (1.34 vs. 2.43, p=0.03).

CONCLUSION

The contrast-to-noise ratio of dark-field images compares more favorably to the contrast-to-noise ratio of transmission images for peripheral lung regions as compared to central regions. For any specific specimen, a calculation of the RCG allows comparing which X-ray modality (dark-field or transmission imaging) produces better contrast-to-noise characteristics in a well-defined ROI.