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Accurate in vivo quantification of airway mucociliary transport (MCT) in animal models is important for understanding diseases such as cystic fibrosis, as well as for developing therapies. A non-invasive method of measuring MCT behaviour, based on tracking the position of micron sized particles using synchrotron x-ray imaging, has previously been described. In previous studies, the location (and path) of each particle was tracked manually, which is a time consuming and subjective process. Here we describe particle tracking methods that were developed to reduce the need for manual particle tracking. The MCT marker particles were detected in the synchrotron x-ray images using cascade classifiers. The particle trajectories along the airway surface were generated by linking the detected locations between frames using a modified particle linking algorithm. The developed methods were compared with the manual tracking method on simulated x-ray images, as well as on in vivo images of rat airways acquired at the SPring-8 Synchrotron. The results for the simulated and in vivo images showed that the semi-automatic algorithm reduced the time required for particle tracking when compared with the manual tracking method, and was able to detect MCT marker particle locations and measure particle speeds more accurately than the manual tracking method. Future work will examine the modification of methods to improve particle detection and particle linking algorithms to allow for more accurate fully-automatic particle tracking.

Faculty and researchers, mostly well-trained, usually fill managerial positions at universities. Still, they do not have formal management training. This qualitative study examined the managerial competencies of 11 university firstline managers. Using Kurz and Bartram’s Great Eight Competency Theory (2002) for the thematic analysis of the interview transcripts, most of the respondents exhibited all eight competencies. However, they differed in terms of manifestations. A typology of academic administrators was developed based on the eight competencies, namely: (1) delegator, (2) accommodator, (3) director, and (4) initiator. Further quantitative research is recommended to refine this typology. Likewise, to develop current and potential administrators, this paper recommends training and workshops on human resources management, communication, conflict resolution, relationship building and maintenance, resource management, mentoring, project and research management, situational analysis, innovation, and the processes of the university.

Propagation-based phase-contrast X-ray computed tomography is a valuable tool for high-resolution visualization of biological samples, giving distinct improvements in terms of contrast and dose requirements compared to conventional attenuation-based computed tomography. Due to its ease of implementation and advances in laboratory X-ray sources, this imaging technique is increasingly being transferred from synchrotron facilities to laboratory environments. This however poses additional challenges, such as the limited spatial coherence and flux of laboratory sources, resulting in worse resolution and higher noise levels. Here we extend a previously developed iterative reconstruction algorithm for this imaging technique to include models for the reduced spatial coherence and the signal spreading of efficient scintillator-based detectors directly into the physical forward model. Furthermore, we employ a noise model which accounts for the full covariance statistics of the image formation process. In addition, we extend the model describing the interference effects such that it now matches the formalism of the widely-used single-material phase-retrieval algorithm, which is based on the sample-homogeneity assumption. We perform a simulation study as well as an experimental study at a laboratory inverse Compton source and compare our approach to the conventional analytical approaches. We find that the modeling of the source and the detector inside the physical forward model can tremendously improve the resolution at matched noise levels and that the modeling of the covariance statistics reduces overshoots (i.e. incorrect increase / decrease in sample properties) at the sample edges significantly.

X-ray imaging has conventionally relied upon attenuation to provide contrast. In recent years, two complementary modalities have been added; (a) phase contrast, which can capture low-density samples that are difficult to see using attenuation, and (b) dark-field x-ray imaging, which reveals the presence of sub-pixel sample structures. These three modalities can be accessed using a crystal analyser, a grating interferometer or by looking at a directly-resolved grid, grating or speckle pattern. Grating and grid-based methods extract a differential phase signal by measuring how far a feature in the illumination has been shifted transversely due to the presence of a sample. The dark-field signal is extracted by measuring how the visibility of the structured illumination is decreased, typically due to the presence of sub-pixel structures in a sample. The strength of the dark-field signal may depend on the grating period, the pixel size and the set-up distances, and additional dark-field signal contributions may be seen as a result of strong phase effects or other factors. In this paper we show that the finite-difference form of the Fokker–Planck equation can be applied to describe the drift (phase signal) and diffusion (dark-field signal) of the periodic or structured illumination used in phase contrast x-ray imaging with gratings, in order to better understand any cross-talk between attenuation, phase and dark-field x-ray signals. In future work, this mathematical description could be used as a basis for new approaches to the inverse problem of recovering both phase and dark-field information.

Bright synchrotron x-ray sources enable imaging with short exposure times, and hence in a high-speed image sequence. These x-ray movies can capture not only sample structure, but also how the sample changes with time, how it functions. The use of a synchrotron x-ray source also provides high spatial coherence, which facilitates the capture of not only a conventional attenuation-based x-ray image, but also phase-contrast and dark-field signals. These signals are strongest from air/tissue interfaces, which means that they are particularly useful for examining the respiratory system. We have performed a range of x-ray imaging studies that look at lung function, airway surface function, inhaled and instilled treatment delivery, and treatment effect in live small animal models [Morgan, 2019]. These have utilized a range of optical set-ups and phase-contrast imaging methods in order to be sensitive to the relevant sample features, and be compatible with high-speed imaging. For example, we have used a grating interferometer to measure how the airsacs in the lung inflate during inhalation, via changes in the dark-field signal [Gradl, 2018], a single-exposure, single-grid set-up to capture changes in the liquid lining of the airways [Morgan, 2015] and propagation-based phase contrast to image clearance of inhaled debris [Donnelley, 2019]. Studies have also utilized a range of analysis methods to extract how the sample features change within a time-sequence of two-dimensional projections or three-dimensional volumes. While these imaging studies began in large-scale synchrotron facilities, we have recently performed these kinds of studies at an inverse-Compton-based compact synchrotron, the Munich Compact Light Source (MuCLS) [Gradl, 2018b]. 1. Morgan, Kaye, et al., “Methods for dynamic synchrotron X-ray imaging of live animals.”, under review 01/2019. 2. Gradl, R., et al. "Dynamic in vivo chest x-ray dark-field imaging in mice." IEEE Transactions on Medical Imaging (2018). 3. Morgan, Kaye S., et al. "In vivo X-ray imaging reveals improved airway surface hydration after a therapy designed for cystic fibrosis." American Journal of Respiratory and Critical Care Medicine 190.4 (2014): 469-472. 4. Donnelley, Martin, et al. "Live-pig-airway surface imaging and whole-pig CT at the Australian Synchrotron Imaging and Medical Beamline." Journal of Synchrotron Radiation 26.1 (2019). 5. Gradl, Regine, et al. "In vivo Dynamic Phase-Contrast X-ray Imaging using a Compact Light Source." Scientific Reports 8.1 (2018b): 6788.

We present a pixel-specific, measurement-driven correction that effectively reduces errors in detector response that give rise to the ring artifacts commonly seen in X-ray computed tomography (CT) scans. This correction is easy to implement, suppresses CT artifacts significantly, and is effective enough for use with both absorption and phase contrast imaging. It can be used as a standalone correction or in conjunction with existing ring artifact removal algorithms to further improve image quality. We validate this method using two X-ray CT data sets acquired using monochromatic sources, showing post-correction signal-to-noise increases of up to 55%, and we define an image quality metric to use specifically for the assessment of ring artifact suppression.

X-rays enable non-invasive and high-resolution imaging that has become central to medical diagnostics and security. While conventional x-ray imaging captures only strongly-attenuating materials like bone or metal, in recent years new x-ray modalities have been developed that can capture weakly-attenuating materials. In particular, variations in x-ray phase can reveal soft tissue structures like the lungs and incoherent scattering of x-rays can describe sub-pixel structures like fine powders. Most techniques that can capture these image modalities require precision optics to convert the phase and incoherent scattering effects to measurable variations in the image intensity, and use multiple exposures to separate the effects. Recent work has been able to extract the three modalities using a single exposure (enabling dynamic and low-dose imaging) and without the need for precision optics (reducing the cost of a set-up). This is possible using structured x-ray illumination and post-measurement computational analysis. The x-ray illumination can be either a grid-like periodic pattern [1,2], or a completely random pattern, such as the pattern produced when a piece of sandpaper is placed in the x-ray beam [3]. Local shifts in the illumination pattern result from x-ray phase variations, and a ‘blurring-out’ of the illumination pattern indicates the presence of sub-pixel structures that scatter the x-ray light. This talk will describe these new methods of x-ray imaging, touching on mathematical models that predict the wavefield behavior, methods of computational analysis and applications to biomedical research [4]. [1] K. Morgan, T. Petersen, M. Donnelley, et al., Optics Express 24 (2016). [2] K. Morgan, P. Modregger, S. Irvine, et al., Optics Letters, 38 (2013). [3] K. Morgan, D. Paganin and K. Siu, Applied Physics Letters 100 (2012). [4] K. Morgan, M. Donnelley, N. Farrow et al., AJRCCM 190 (2014).