CAD-ASTRA: a versatile and efficient mesh projector for X-ray tomography with the ASTRA-toolbox.

Accurate and fast simulation of X-ray projection data from mesh models has many applications in academia and industry, ranging from 3D X-ray computed tomography (XCT) reconstruction algorithms to radiograph-based object inspection and quality control. While software tools for the simulation of X-ray projection data from mesh models are available, they lack either performance, public availability, flexibility to implement non-standard scanning geometries, or easy integration with existing 3D XCT software. In this paper, we propose CAD-ASTRA, a highly versatile toolbox for fast simulation of X-ray projection data from mesh models. While fully functional as standalone software, it is also compatible with the ASTRA toolbox, an open-source toolbox for flexible tomographic reconstruction. CAD-ASTRA provides three specialized GPU projectors based on state-of-the-art algorithms for 3D rendering, implemented using the NVIDIA CUDA Toolkit and the OptiX engine. First, it enables X-ray phase contrast simulations by modeling refraction through ray tracing. Second, it allows the back-propagation of projective errors to mesh vertices, enabling immediate application in mesh reconstruction, deep learning, and other optimization routines. Finally, CAD-ASTRA allows simulation of polychromatic X-ray projections from heterogeneous objects with a source of finite focal spot size. Use cases on a CAD-based inspection task, a phase contrast experiment, a combined mesh-volumetric data projection, and a mesh reconstruction demonstrate the wide applicability of CAD-ASTRA.

Joint multi-contrast CT for edge illumination X-ray phase contrast imaging using split Barzilai-Borwein steps.

Edge illumination (EI) is an X-ray imaging technique that, in addition to conventional absorption contrast, provides refraction and scatter contrast. It relies on an absorption mask in front of the sample that splits the X-ray beam into beamlets, which hits a second absorption mask positioned in front of the detector. The sample mask is then shifted in multiple steps with respect to the detector mask, thereby measuring an illumination curve per detector element. The width, position, and area of this curve estimated with and without the sample in the beam is then compared, which ultimately provides absorption, refraction, and scatter contrast for each detector pixel. From the obtained contrast sinograms, three contrast tomograms can be computed. In summary, conventional EI relies on a two-stage process comprised of a computational and time intensive contrast retrieval process, followed by tomographic reconstruction. In this work, a novel joint reconstruction method is proposed, which utilizes a combined forward model to reconstruct the three contrasts simultaneously, without the need for an intermediate contrast retrieval step. Compared to the state-of-the-art, this approach reduces reconstruction times, as the retrieval step is skipped and allows a much more flexible acquisition scheme, as there is no need to sample a full illumination curve at each projection angle. The proposed method is shown to improve reconstruction quality on subsampled datasets, enabling the reconstruction of three contrasts from single-shot datasets.

A Condensed History Approach to X-Ray Dark Field Effects in Edge Illumination Phase Contrast Simulations.

X-ray dark field signals, measurable in many x-ray phase contrast imaging (XPCI) setups, stem from unresolvable microstructures in the scanned sample. This makes them ideally suited for the detection of certain pathologies, which correlate with changes in the microstructure of a sample. Simulations of x-ray dark field signals can aid in the design and optimization of XPCI setups, and the development of new reconstruction techniques. Current simulation tools, however, require explicit modelling of the sample microstructures according to their size and spatial distribution. This process is cumbersome, does not translate well between different samples, and considerably slows down simulations. In this work, a condensed history approach to modelling x-ray dark field effects is presented, under the assumption of an isotropic distribution of microstructures, and applied to edge illumination phase contrast simulations. It substantially simplifies the sample model, can be easily ported between samples, and is two orders of magnitude faster than conventional dark field simulations, while showing equivalent results.Clinical relevance- Dark field signal provides information on the microstructure distribution within the investigated sample, which can be applied in areas such as histology and lung x-ray imaging. Efficient simulation tools for this dark field signal aid in optimizing scanning setups, acquisition schemes and reconstruction techniques.

Automatic processing of multilingual medical terminology: applications to thesaurus enrichment and cross-language information retrieval.

OBJECTIVES: We present in this article experiments on multi-language information extraction and access in the medical domain. For such applications, multilingual terminology plays a crucial role when working on specialized languages and specific domains. MATERIAL AND METHODS: We propose firstly a method for enriching multilingual thesauri which extracts new terms from parallel corpora, and secondly, a new approach for bilingual lexicon extraction from comparable corpora, which uses a bilingual thesaurus as a pivot. We illustrate their use in multi-language information retrieval (English/German) in the medical domains. RESULTS: Our experiments show that these automatically extracted bilingual lexicons are accurate enough (85% precision for term extraction) for semi-automatically enriching mono- or bi-lingual thesauri such as the universal medical language system, and that their use in cross-language information retrieval significantly improves the retrieval performance (from 22 to 40% average precision) and clearly outperforms existing bilingual lexicon resources (both general lexicons and specialized ones). CONCLUSION: We show in this paper first that bilingual lexicon extraction from parallel corpora in the medical domain could lead to accurate, specialized lexicons, which can be used to help enrich existing thesauri and second that bilingual lexicons extracted from comparable corpora outperform general bilingual resources for cross-language information retrieval.

Baseline cytosolic Ca2+ oscillations derived from a non-endoplasmic reticulum Ca2+ store.

Cytosolic Ca(2+) oscillations can be due to cycles of release and re-uptake of internally stored Ca(2+). To investigate the nature of these Ca(2+) stores, we expressed the Pmr1 Ca(2+) pump of Caenorhabditis elegans in COS-1 cells and pretreated the cells with thapsigargin to prevent Ca(2+) uptake by the sarco(endo)plasmic reticulum Ca(2+)-ATPase. Pmr1 co-localized with the Golgi-specific 58K protein and was targeted to a Ca(2+) store that was less leaky for Ca(2+) than the endoplasmic reticulum and whose inositol trisphosphate receptors were less sensitive to inositol trisphosphate and ATP than those in the endoplasmic reticulum. ATP-stimulated Pmr1-overexpressing cells responded after a latency to extracellular Ca(2+) with a regenerative Ca(2+) signal, which could be prevented by caffeine. They also produced very stable ilimaquinone-sensitive baseline Ca(2+) spikes, even in the presence of thapsigargin. Such responses never occurred in non-transfected cells or in cells that overexpressed the type-1 sarco(endo)plasmic reticulum Ca(2+)-ATPase. Abortive Ca(2+) spikes also occurred in histamine-stimulated untransfected HeLa cells pretreated with thapsigargin, and they too were inhibited by ilimaquinone. We conclude that the Pmr1-induced Ca(2+) store, which probably corresponds to the Golgi compartment, can play a crucial role in setting up baseline Ca(2+) spiking.

Hybrid methods using genetic algorithms for global optimization.

This paper discusses the trade-off between accuracy, reliability and computing time in global optimization. Particular compromises provided by traditional methods (Quasi-Newton and Nelder-Mead's simplex methods) and genetic algorithms are addressed and illustrated by a particular application in the field of nonlinear system identification. Subsequently, new hybrid methods are designed, combining principles from genetic algorithms and "hill-climbing" methods in order to find a better compromise to the trade-off. Inspired by biology and especially by the manner in which living beings adapt themselves to their environment, these hybrid methods involve two interwoven levels of optimization, namely evolution (genetic algorithms) and individual learning (Quasi-Newton), which cooperate in a global process of optimization. One of these hybrid methods appears to join the group of state-of-the-art global optimization methods: it combines the reliability properties of the genetic algorithms with the accuracy of Quasi-Newton method, while requiring a computation time only slightly higher than the latter.

Phosphoinositides in barley aleurone layers and gibberellic Acid-induced changes in metabolism.

Phospholipids of barley (Hordeum vulgare L. cv Himalaya) aleurone layers were labeled with myo-[2-(3)H]inositol or [(32)Pi], extracted, and analyzed by physical (chromatography) and chemical (deacylation) techniques. Three phospholipids were found to incorporate both myo-[2-(3)H]inositol and [(32)Pi]-phosphatidylinositol, phosphatidylinositol-monophosphate, and phosphatidylinositol-bisphosphate. Stimulation of [(3)H]inositol prelabeled aleurone layers with GA(3) showed enhanced incorporation of label into phosphatidylinositol within 30 seconds and subsequent rapid breakdown. Stimulation of phosphatidylinositol labeling observed in these studies is the earliest response of aleurone cells to gibberellic acid reported.