Helical sample-stepping for faster speckle-based multi-modal tomography with the Unified Modulated Pattern Analysis (UMPA) model

Speckle-based imaging (SBI) is a multi-modal X-ray imaging technique that gives access to absorption, phase-contrast, and dark-field signals from a single dataset. However, it is often difficult to disentangle the different signals from a single measurement. Having complementary data obtained by repeating the scan under slightly varied conditions (multiframe approach) can significantly enhance the accuracy of signal extraction and, consequently, improve the overall quality of the final reconstruction. In order to retrieve the different channels, SBI relies on a reference pattern, generated by the addition of a wavefront marker in the beam (i.e., a sandpaper or gratings). Here, we show how a continuous helical acquisition can extend the field of view (FOV) and speed up the acquisition while maintaining a multiframe approach for the signal retrieval of a test object

Multi-Modal X-ray Imaging and Analysis for Characterization of Urinary Stones

Backgound: The composition of stones formed in the urinary tract plays an important role in their management over time. The most common imaging method for the non-invasive evaluation of urinary stones is radiography and computed tomography (CT). However, CT is not very sensitive, and cannot differentiate between all critical stone types. In this study, we propose the application, and evaluate the potential, of a multi-modal (or multi-contrast) X-ray imaging technique called speckle-based imaging (SBI) to differentiate between various types of urinary stones. Methods: Three different stone samples were extracted from animal and human urinary tracts and examined in a laboratory-based speckle tracking setup. The results were discussed based on an X-ray diffraction analysis and a comparison with X-ray microtomography and grating-based interferometry. Results: The stones were classified through compositional analysis by X-ray diffraction. The multi-contrast images obtained using the SBI method provided detailed information about the composition of various urinary stone types, and could differentiate between them. X-ray SBI could provide highly sensitive and high-resolution characterizations of different urinary stones in the radiography mode, comparable to those by grating interferometry. Conclusions: This investigation demonstrated the capability of the SBI technique for the non-invasive classification of urinary stones through radiography in a simple and cost-effective laboratory setting. This opens the possibility for further studies concerning full-field in vivo SBI for the clinical imaging of urinary stones

IDENTIFIKASI PAPARAN RADIASI X-RAY UNTUK KESELAMATAN RADIASI MENGGUNAKAN RANDOM FOREST CLASSIFICATION

The safety level of X-ray exposure is very important because it has short-term and long-term effects that significantly affect the health of radiation workers and the surrounding environment. Measurements of the safety level of X-Ray radiation are generally carried out using conventional methods, namely manually identifying the radiation exposure value data for workers and the surrounding environment from a survey meter, then adding up periodically. However, this can potentially cause errors in the addition so that the method produces less accurate data. This study aims to X-Ray radiation exposure dose using Random Forest Classification. The radiation data processed is the dose value of X-Ray exposure measures using a digital survey meter (in µSv/h) unit of as many as 160 datasets and consists of 87 safe and 73 unsafe doses. Data are classified according to the International Atomic Energy Agency (IAEA) dosage limit value rule. The performance of Random Forest Classification is evaluated with Naïve Bayes dan K-Nearest Neighbor (KNN). The result shows that the Random Forest Classification accuracy value is 90%, the Naïve Bayes accuracy value is 85%, and the KNN accuracy value is 86%. Therefore, the performance value from the Random Forest Classification of 97% is taken as the best result. As a summary of this study, Random Forest Classification performed better than other Naïve Bayes and K-Nearest Neighbor (KNN) for identifying the safety level of X-Ray radiation exposure as proven with the optimum given the parameters applied.  Tingkat keamanan paparan X-Ray sangat penting karena mempunyai dampak jangka pendek dan jangka panjang yang sangat mempengaruhi kesehatan pekerja radiasi dan lingkungan sekitarnya. Pengukuran tingkat keamanan radiasi X-Ray pada umumnya dilakukan dengan cara konvensional, yaitu mengidentifikasi secara manual data nilai paparan radiasi bagi pekerja dan lingkungan sekitar dari survey meter, kemudian dijumlahkan secara berkala. Namun hal ini berpotensi menimbulkan kesalahan dalam penambahan sehingga metode menghasilkan data yang kurang akurat. Penelitian ini bertujuan untuk mengetahui dosis paparan radiasi X-Ray menggunakan Random Forest Classification. Data radiasi yang diolah merupakan nilai dosis pengukuran paparan X-Ray dengan menggunakan survey meter digital (dalam µSv/h) sebanyak 160 data set dan terdiri dari 87 dosis aman dan 73 dosis tidak aman. Data diklasifikasikan menurut aturan nilai batas dosis International Atomic Energy Agency (IAEA). Kinerja Random Forest Classification dievaluasi dengan Naïve Bayes dan K-Nearest Neighbor (KNN). Hasil penelitian menunjukkan nilai akurasi Random Forest Classification sebesar 90%, nilai akurasi Naïve Bayes sebesar 85%, dan nilai akurasi KNN sebesar 86%. Oleh karena itu, nilai kinerja dari Random Forest Classification sebesar 97% diambil sebagai hasil terbaik. Sebagai rangkuman penelitian ini, Random Forest Classification berkinerja lebih baik dibandingkan Naïve Bayes dan K-Nearest Neighbor (KNN) lainnya dalam mengidentifikasi tingkat keamanan paparan radiasi X-Ray yang terbukti secara optimal berdasarkan parameter yang diterapkan

High-speed processing of X-ray wavefront marking data with the Unified Modulated Pattern Analysis (UMPA) model

Wavefront-marking X-ray imaging techniques use e.g., sandpaper or a grating to generate intensity fluctuations, and analyze their distortion by the sample in order to retrieve attenuation, phase-contrast, and dark-field information. Phase contrast yields an improved visibility of soft-tissue specimens, while dark-field reveals small-angle scatter from sub-resolution structures. Both have found many biomedical and engineering applications. The previously developed Unified Modulated Pattern Analysis (UMPA) model extracts these modalities from wavefront-marking data. We here present a new UMPA implementation, capable of rapidly processing large datasets and featuring capabilities to greatly extend the field of view. We also discuss possible artifacts and additional new features.Comment: 18 pages, 7 figures, submitted to Optics Expres

Multimodal Intrinsic Speckle-Tracking (MIST) to extract rapidly-varying diffuse X-ray scatter

Speckle-based phase-contrast X-ray imaging (SB-PCXI) can reconstruct high-resolution images of weakly-attenuating materials that would otherwise be indistinguishable in conventional attenuation-based imaging. The experimental setup of SB-PCXI requires only a sufficiently coherent source and spatially random mask, positioned between the source and detector. The technique can extract sample information at length scales smaller than the imaging system's spatial resolution; this enables multimodal signal reconstruction. ``Multimodal Intrinsic Speckle-Tracking'' (MIST) is a rapid and deterministic formalism derived from the paraxial-optics form of the Fokker-Planck equation. MIST simultaneously extracts attenuation, refraction, and small-angle scattering (diffusive-dark-field) signals from a sample and is more computationally efficient compared to alternative speckle-tracking approaches. Hitherto, variants of MIST have assumed the diffusive-dark-field signal to be spatially slowly varying. Although successful, these approaches have been unable to well-describe unresolved sample microstructure whose statistical form is not spatially slowly varying. Here, we extend the MIST formalism such that there is no such restriction, in terms of a sample's rotationally-isotropic diffusive-dark-field signal. We reconstruct multimodal signals of two samples, each with distinct X-ray attenuation and scattering properties. The reconstructed diffusive-dark-field signals have superior image quality compared to our previous approaches which assume the diffusive-dark-field to be a slowly varying function of transverse position. Our generalisation may assist increased adoption of SB-PCXI in applications such as engineering and biomedical disciplines, forestry, and palaeontology, and is anticipated to aid the development of speckle-based diffusive-dark-field tensor tomography.Comment: 18 pages, 7 figure

Dark-field tomography of an attenuating object using intrinsic x-ray speckle tracking.

Purpose: We investigate how an intrinsic speckle tracking approach to speckle-based x-ray imaging is used to extract an object's effective dark-field (DF) signal, which is capable of providing object information in three dimensions. Approach: The effective DF signal was extracted using a Fokker-Planck type formalism, which models the deformations of illuminating reference beam speckles due to both coherent and diffusive scatter from the sample. Here, we assumed that (a) small-angle scattering fans at the exit surface of the sample are rotationally symmetric and (b) the object has both attenuating and refractive properties. The associated inverse problem of extracting the effective DF signal was numerically stabilized using a "weighted determinants" approach. Results: Effective DF projection images, as well as the DF tomographic reconstructions of the wood sample, are presented. DF tomography was performed using a filtered back projection reconstruction algorithm. The DF tomographic reconstructions of the wood sample provided complementary, and otherwise inaccessible, information to augment the phase contrast reconstructions, which were also computed. Conclusions: An intrinsic speckle tracking approach to speckle-based imaging can tomographically reconstruct an object's DF signal at a low sample exposure and with a simple experimental setup. The obtained DF reconstructions have an image quality comparable to alternative x-ray DF techniques

Functional and multiscale 3D structural investigation of brain tissue through correlative in vivo physiology, synchrotron microtomography and volume electron microscopy

Understanding the function of biological tissues requires a coordinated study of physiology and structure, exploring volumes that contain complete functional units at a detail that resolves the relevant features. Here, we introduce an approach to address this challenge: Mouse brain tissue sections containing a region where function was recorded using in vivo 2-photon calcium imaging were stained, dehydrated, resin-embedded and imaged with synchrotron X-ray computed tomography with propagation-based phase contrast (SXRT). SXRT provided context at subcellular detail, and could be followed by targeted acquisition of multiple volumes using serial block-face electron microscopy (SBEM). In the olfactory bulb, combining SXRT and SBEM enabled disambiguation of in vivo-assigned regions of interest. In the hippocampus, we found that superficial pyramidal neurons in CA1a displayed a larger density of spine apparati than deeper ones. Altogether, this approach can enable a functional and structural investigation of subcellular features in the context of cells and tissues

X-ray Phase Contrast Tomography : Setup and Scintillator Development

X-ray microscopy and micro-tomography (μCT) are valuable non-destructive examination methods in many disciplines such as bio-medical research, archaeometry, material science and paleontology. Besides being implemented at synchrotrons radiation sources, laboratory setups using an X-ray tube and high-resolution scintillation detector routinely provide information on the micrometre scale. To improve the image contrast for small and low-density samples, it is possible to introduce a propagation distance between sample and detector to perform propagation-based phase contrast imaging (PB-PCI). This contrast mode relies on a sufficiently coherent illumination and is characterised by the appearance of an additional intensity modulations (‘edge enhancement fringes’) around interfaces in the image. The strength of this effect depends on hardware as well as geometry parameters. This thesis describes the development of a laboratory setup for X-ray μCT with a PB-PCI option. It contains the theoretical and technical background of the setup design as well the characterization of the achieved performance.Moreover, the optimization of the PB-PCI geometry was explored both theoretically as well as experimentally for three different setups. A simple rule for finding the optimal magnification to achieve high phase contrast for edge features was deduced. The effect of the polychromatic source spectrum und detector sensitivity was identified and included into the theoretical model.Besides application and methodological studies, the setup was used to test and characterise new X-ray scintillator materials. Recently, metal halide perovskite nanocrystals (MHP NCs) have gained attention due to their outstanding opto-electronic performance. The main challenge for their use and commercialization is their low long-term stability against humidity, temperature, and light exposure. Here, a CsPbBr3 scintillator comprised of an ordered array of nanowires (NW) in an anodized aluminium oxide (AAO) membrane is presented as a promising new scintillator for X-ray microscopy and μCT. It shows a high light yield under X-ray exposure which improves with smaller NW diameter and higher NW length. In contrast to many other MHP materials this scintillator shows good stability under continuous X-ray exposure and changing environmental conditions over extended time spans of several weeks. This makes it suitable for tomography, which is demonstrated by acquiring the first high-resolution tomogram using a MHP scintillator with the presented laboratory setup