Dose fractionation in synchrotron radiation x-ray phase micro-tomography

Automatic Differentiation for Inverse Problems in X-ray Imaging and Microscopy

Computational techniques allow breaking the limits of traditional imaging methods, such as time restrictions, resolution, and optics flaws. While simple computational methods can be enough for highly controlled microscope setups or just for previews, an increased level of complexity is instead required for advanced setups, acquisition modalities or where uncertainty is high; the need for complex computational methods clashes with rapid design and execution. In all these cases, Automatic Differentiation, one of the subtopics of Artificial Intelligence, may offer a functional solution, but only if a GPU implementation is available. In this paper, we show how a framework built to solve just one optimisation problem can be employed for many different X-ray imaging inverse problems.

In vivo monitoring of bone microstructure by propagation-based phase-contrast computed tomography using monochromatic synchrotron light

Hard X-ray phase-contrast imaging is sensitive to density variation in objects and shows a dose advantage for in vivo observation over absorption-contrast imaging. We examined the capability of propagation-based phase-contrast tomography (PB-PCT) with single-distance phase retrieval for tracking of bone structure and mineral changes using monochromatic synchrotron light. Female mice underwent ovariectomy and drill-hole surgery in the right tibial diaphysis and were divided into two groups: OVX and OVX-E (n = 6 each); the latter group was treated with intraperitoneal administration of 14,15-epoxyeicosatrienoic acid (14,15-EET) for promoting bone repair. Age-matched mice subjected to sham ovariectomy and drill-hole surgery (Sham) were also prepared (n = 6). In vivo CT scans of the drilled defect were acquired 3, 7, and 11 days after surgery, and tomographic images were matched by three-dimensional registration between successive time points for monitoring the process of defect filling. In addition, using absorption-contrast CT as the reference method, the validity of PB-PCT was evaluated in one mouse by comparing images of tibial metaphyseal bone between the two methods in terms of bone geometry as well as the measure of mineralization. Although phase retrieval is strictly valid only for single-material objects, PB-PCT, with its lower radiation dose, could provide a depiction of bone structure similar to that from absorption-contrast CT. There was a significant correlation of linear absorption coefficients between the two methods, indicating the possibility of a rough estimate of the measure of mineralization by PB-PCT. Indeed, delayed bone regeneration (OVX vs. Sham) and the efficacy of 14,15-EET for improving osteoporotic bone repair (OVX-E vs. OVX) could be detected in both bone volume and mineralization by PB-PCT. Thus, in combination with single-distance phase retrieval, PB-PCT would have great potential for providing a valuable tool to track changes in bone structure and mineralization, and for evaluating the effects of therapeutic interventions as well.

Registration of phase-contrast images in propagation-based X-ray phase tomography

X-ray phase tomography aims at reconstructing the 3D electron density distribution of an object. It offers enhanced sensitivity compared to attenuation-based X-ray absorption tomography. In propagation-based methods, phase contrast is achieved by letting the beam propagate after interaction with the object. The phase shift is then retrieved at each projection angle, and subsequently used in tomographic reconstruction to obtain the refractive index decrement distribution, which is proportional to the electron density. Accurate phase retrieval is achieved by combining images at different propagation distances. For reconstructions of good quality, the phase-contrast images recorded at different distances need to be accurately aligned. In this work, we characterise the artefacts related to misalignment of the phase-contrast images, and investigate the use of different registration algorithms for aligning in-line phase-contrast images. The characterisation of artefacts is done by a simulation study and comparison with experimental data. Loss in resolution due to vibrations is found to be comparable to attenuation-based computed tomography. Further, it is shown that registration of phase-contrast images is nontrivial due to the difference in contrast between the different images, and the often periodical artefacts present in the phase-contrast images if multilayer X-ray optics are used. To address this, we compared two registration algorithms for aligning phase-contrast images acquired by magnified X-ray nanotomography: one based on cross-correlation and one based on mutual information. We found that the mutual information-based registration algorithm was more robust than a correlation-based method.