Enhanced and Flexible Software Tools for X-ray Computed Tomography at the Italian Synchrotron Radiation Facility Elettra

X-ray computed tomography (CT) experiments performed at synchrotron radiation facilities require adequate computing and storage resources due to the large amount of acquired and reconstructed data produced. To satisfy the heterogeneous needs of beamline users, flexible solutions are also required. Moreover, the growing demand of quantitative image analysis impose an easy integration between the CT reconstruction process and the subsequent feature extraction step. This paper presents some of the software solutions adopted by the SYRMEP beamline of the Italian synchrotron radiation facility Elettra. By using the enhanced version of the reconstruction software here presented as well as data reduction and data analysis tools, beamline users can easily implement an integrated and comprehensive approach to the digital image processing and image analysis required by a tomography-oriented scientific workflow

SYRMEP Tomo Project: a graphical user interface for customizing CT reconstruction workflows

8When considering the acquisition of experimental synchrotron radiation (SR) X-ray CT data, the reconstruction workflow cannot be limited to the essential computational steps of flat fielding and filtered back projection (FBP). More refined image processing is often required, usually to compensate artifacts and enhance the quality of the reconstructed images. In principle, it would be desirable to optimize the reconstruction workflow at the facility during the experiment (beamtime). However, several practical factors affect the image reconstruction part of the experiment and users are likely to conclude the beamtime with sub-optimal reconstructed images. Through an example of application, this article presentsSYRMEP Tomo Project(STP), an open-source software tool conceived to let users design custom CT reconstruction workflows. STP has been designed for post-beamtime (off-line use) and for a new reconstruction of past archived data at user's home institution where simple computing resources are available. Releases of the software can be downloaded at the Elettra Scientific Computing group GitHub repository https://github.com/ElettraSciComp/STP-Gui.openopenBrun, Francesco; Massimi, Lorenzo; Fratini, Michela; Dreossi, Diego; Billé, Fulvio; Accardo, Agostino; Pugliese, Roberto; Cedola, AlessiaBrun, Francesco; Massimi, Lorenzo; Fratini, Michela; Dreossi, Diego; Billé, Fulvio; Accardo, Agostino; Pugliese, Roberto; Cedola, Alessi

Optimization of propagation-based x-ray phase-contrast tomography for breast cancer imaging

The aim of this study was to optimise the experimental protocol and data analysis for in-vivo breast cancer X-ray imaging. Results are presented of the experiment at the SYRMEP beamline of Elettra Synchrotron using the propagation-based phase-contrast mammographic tomography method, which incorporates not only absorption, but also X-ray phase information. In this study the images of breast tissue samples, of a size corresponding to a full human breast, with radiologically acceptable X-ray doses were obtained, and the degree of improvement of the image quality (from the diagnostic point of view) achievable using propagation-based phase-contrast image acquisition protocols with proper incorporation of X-ray phase retrieval into the reconstruction pipeline was investigated. Parameters such as the X-ray energy, sample-to-detector distance and data processing methods were tested, evaluated and optimized with respect to the estimated diagnostic value using a mastectomy sample with a malignant lesion. The results of quantitative evaluation of images were obtained by means of radiological assessment carried out by 13 experienced specialists. A comparative analysis was performed between the X-ray and the histological images of the specimen. The results of the analysis indicate that, within the investigated range of parameters, both the objective image quality characteristics and the subjective radiological scores of propagation-based phase-contrast images of breast tissues monotonically increase with the strength of phase contrast which in turn is directly proportional to the product of the radiation wavelength and the sample-to-detector distance. The outcomes of this study serve to define the practical imaging conditions and the CT reconstruction procedures appropriate for low-dose phase-contrast mammographic imaging of live patients at specially designed synchrotron beamlines

Machine learning-based automated segmentation with a feedback loop for 3D synchrotron micro-CT

Die Entwicklung von Synchrotronlichtquellen der dritten Generation hat die Grundlage für die Untersuchung der 3D-Struktur opaker Proben mit einer Auflösung im Mikrometerbereich und höher geschaffen. Dies führte zur Entwicklung der Röntgen-Synchrotron-Mikro-Computertomographie, welche die Schaffung von Bildgebungseinrichtungen zur Untersuchung von Proben verschiedenster Art förderte, z.B. von Modellorganismen, um die Physiologie komplexer lebender Systeme besser zu verstehen. Die Entwicklung moderner Steuerungssysteme und Robotik ermöglichte die vollständige Automatisierung der Röntgenbildgebungsexperimente und die Kalibrierung der Parameter des Versuchsaufbaus während des Betriebs. Die Weiterentwicklung der digitalen Detektorsysteme führte zu Verbesserungen der Auflösung, des Dynamikbereichs, der Empfindlichkeit und anderer wesentlicher Eigenschaften. Diese Verbesserungen führten zu einer beträchtlichen Steigerung des Durchsatzes des Bildgebungsprozesses, aber auf der anderen Seite begannen die Experimente eine wesentlich größere Datenmenge von bis zu Dutzenden von Terabyte zu generieren, welche anschließend manuell verarbeitet wurden. Somit ebneten diese technischen Fortschritte den Weg für die Durchführung effizienterer Hochdurchsatzexperimente zur Untersuchung einer großen Anzahl von Proben, welche Datensätze von besserer Qualität produzierten. In der wissenschaftlichen Gemeinschaft besteht daher ein hoher Bedarf an einem effizienten, automatisierten Workflow für die Röntgendatenanalyse, welcher eine solche Datenlast bewältigen und wertvolle Erkenntnisse für die Fachexperten liefern kann. Die bestehenden Lösungen für einen solchen Workflow sind nicht direkt auf Hochdurchsatzexperimente anwendbar, da sie für Ad-hoc-Szenarien im Bereich der medizinischen Bildgebung entwickelt wurden. Daher sind sie nicht für Hochdurchsatzdatenströme optimiert und auch nicht in der Lage, die hierarchische Beschaffenheit von Proben zu nutzen. Die wichtigsten Beiträge der vorliegenden Arbeit sind ein neuer automatisierter Analyse-Workflow, der für die effiziente Verarbeitung heterogener Röntgendatensätze hierarchischer Natur geeignet ist. Der entwickelte Workflow basiert auf verbesserten Methoden zur Datenvorverarbeitung, Registrierung, Lokalisierung und Segmentierung. Jede Phase eines Arbeitsablaufs, die eine Trainingsphase beinhaltet, kann automatisch feinabgestimmt werden, um die besten Hyperparameter für den spezifischen Datensatz zu finden. Für die Analyse von Faserstrukturen in Proben wurde eine neue, hochgradig parallelisierbare 3D-Orientierungsanalysemethode entwickelt, die auf einem neuartigen Konzept der emittierenden Strahlen basiert und eine präzisere morphologische Analyse ermöglicht. Alle entwickelten Methoden wurden gründlich an synthetischen Datensätzen validiert, um ihre Anwendbarkeit unter verschiedenen Abbildungsbedingungen quantitativ zu bewerten. Es wurde gezeigt, dass der Workflow in der Lage ist, eine Reihe von Datensätzen ähnlicher Art zu verarbeiten. Darüber hinaus werden die effizienten CPU/GPU-Implementierungen des entwickelten Workflows und der Methoden vorgestellt und der Gemeinschaft als Module für die Sprache Python zur Verfügung gestellt. Der entwickelte automatisierte Analyse-Workflow wurde erfolgreich für Mikro-CT-Datensätze angewandt, die in Hochdurchsatzröntgenexperimenten im Bereich der Entwicklungsbiologie und Materialwissenschaft gewonnen wurden. Insbesondere wurde dieser Arbeitsablauf für die Analyse der Medaka-Fisch-Datensätze angewandt, was eine automatisierte Segmentierung und anschließende morphologische Analyse von Gehirn, Leber, Kopfnephronen und Herz ermöglichte. Darüber hinaus wurde die entwickelte Methode der 3D-Orientierungsanalyse bei der morphologischen Analyse von Polymergerüst-Datensätzen eingesetzt, um einen Herstellungsprozess in Richtung wünschenswerter Eigenschaften zu lenken

Machine learning denoising of high-resolution X-ray nanotomography data

High-resolution X-ray nano­tomography is a quantitative tool for investigating specimens from a wide range of research areas. However, the quality of the reconstructed tomogram is often obscured by noise and therefore not suitable for automatic segmentation. Filtering methods are often required for a detailed quantitative analysis. However, most filters induce blurring in the reconstructed tomograms. Here, machine learning (ML) techniques offer a powerful alternative to conventional filtering methods. In this article, we verify that a self-supervised denoising ML technique can be used in a very efficient way for eliminating noise from nano­tomography data. The technique presented is applied to high-resolution nano­tomography data and compared to conventional filters, such as a median filter and a nonlocal means filter, optimized for tomographic data sets. The ML approach proves to be a very powerful tool that outperforms conventional filters by eliminating noise without blurring relevant structural features, thus enabling efficient quantitative analysis in different scientific fields

A Multi-Material Approach to Beam Hardening Correction and Calibration in X-Ray Microtomography

PhDX-ray microtomogaphy is a non-clinical, non-destructive, and quantitative technique for determining three-dimensional mineral concentration distributions in variably radiolucent samples with a spatial resolution on the micron scale. For reasons of practicality, particularly for longterm studies, it is often not possible or desirable to utilise a monochromatic X-ray source and so microtomography using a conventional impact-source X-ray generator to produce a polychromatic photon beam is carried out instead. The use of photons of multiple energies causes the production of projection artefacts arising from preferential absorption, which impair the greyscale accuracy of the resulting reconstruction and the material concentration measurements that are derived from the linear attenuation coefficients (LACs). The purpose of the project described in this thesis is to identify weaknesses in the current method of beam hardening correction and to develop and test a tomographic calibration and projection processing method which may demonstrably improve the quality of current beam hardening correction methods as used with the MuCAT microtomography equipment, which provides a worldclass impact-source microtomography research and production facility at Barts and The London School of Medicine and Dentistry. An overview of the physical basis of X-ray computed tomography and X-ray microtomography is given from first principles, and examples of quantitative applications of the techniques, which generally depend on accurate reconstruction of linear attenuation coefficient values, are discussed. The major sources of artefacts in X-ray microtomography are discussed, particularly those with a direct impact on reconstructed linear attenuation coefficient values. Beam hardening is identified as an error source of particular interest, with secondary research on the effects of any beam hardening correction method on the severity of Compton scatter artefacts, and a critical review is carried out of historical attempts to reduce or mitigate these artefacts, particularly the single-material parameter-optimisation approach in service at the beginning of the research project. A ‘carousel’ test piece comprising multiple attenuators of multiple materials along with attenuation optimisation software based on varying multiple system parameters in order to extend the functionality and usability of the existing correction model, and qualitative results have so far been gathered suggesting the use of this system over the pre-existing attenuation wedge and parameter-optimisation method. A study of the effects of tuning the photon energy to which calibrations are made is carried out, showing improved linear attenuation coefficient recovery at a higher energy than was previously believed to be optimal, and a significant effect arising from X-ray generator target evaporation leading to spatial changes and time-dependence of the target thickness parameter is measured, suggesting that automated calibration as a standard part of the measurement process is required. A stability experiment is carried out using this method in order to examine the possibility of inconsistency resulting from ageing of the filament cathode, which is found not to significantly impact the quality of results. An immersion tank is developed in order to ensure beam hardening correction validity in the case of dual-material specimens where a radiodensity-matching fluid can be provided and the sample is suitable for immersion. Experimental comparison using a commercial beam hardening calibration device as the specimen reveals significantly improved hydroxyapatite concentration measurement recovery. An in-scatter experiment was carried out on the immersion tank, and it was found that there was a significant scatter contribution when the tank was filled in the case where the sample thickness is much less than the tank thickness. Proposals are presented for further work to improve reconstruction quality through of scatter reduction techniques in impactsource microtomographic systems, and to utilise the immersion tank for in situ chemical erosion experiments. The effects of the improvements to the beam hardening process are demonstrated using a biological specimen to demonstrate qualitative changes in reconstruction, particularly in improved dark levels surrounding the specimen. A second experiment is carried out in order to test the reproducibility of results, which is found to be improved by approximately four times over the same dataset corrected using the pre-existingbeam-hardening calibration methodEngineering and Physical Sciences Research Council grant number EP/G007845/1

Development of algorithms and methods for three-dimensional image analysis and biomedical applications

2010/2011Tomographic imaging is both the science and the tool to explore the internal structure of objects. The mission is to use images to characterize the static and/or dynamic properties of the imaged object in order to further integrate these properties into principles, laws or theories. Among the recent trends in tomographic imaging, three- dimensional (3D) methods are gaining preference and there is the quest for overcoming the bare qualitative observation towards the extraction of quantitative parameters directly from the acquired images. To this aim, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), as well as the related micro-scale techniques (μ-CT and μ-MRI), are promising tools for all the fields of science in which non-destructive tests are required. In order to support the interpretation of the images produced by these techniques, there is a growing demand of reliable image analysis methods for the specific 3D domain. The aim of this thesis is to present approaches for effective and efficient three-dimensional image analysis with special emphasis on porous media analysis. State-of-the art as well as innovative tools are included in a special software and hardware solution named Pore3D, developed in a collaboration with the Italian 3rd generation synchrotron laboratory Elettra (Basovizza - Trieste, Italy). Algorithms and methods for the characterization of different kinds of porous media are described. The key steps of image segmentation and skeletonization of the segmented pore space are also discussed in depth. Three different clinical and biomedical applications of quantitative analysis of tomographic images are presented. The reported applications have in common the characterization of the micro-architecture of trabecular bone. The trabecular (or cancellous) bone is a 3D mesh- work of bony trabeculae and void spaces containing the bone marrow. It can then be thought of as a porous medium with an interconnected porous space. To be more specific, the first application aims at characterizing a structure (a tissue engineering scaffold) that has to mimic the architecture of trabecular bone. The relevant features of porosity, pore- and throat-size distributions, connectivity and structural anisotropy indexes are automatically extracted from μ-CT images. The second application is based on ex vivo experiments carried out on femurs and lumbar spines of mice affected by microgravity conditions. Wild type and transgenic mice were hosted in the International Space Station (ISS) for 3 months and the observed bone loss due to the near-zero gravity was quantified by means of synchrotron radiation μ-CT image analysis. Finally, the results of an in vivo study on the risk of fracture in osteoporotic subjects is reported. The study is based on texture analysis of high resolution clinical magnetic resonance (MR) images.XXIV Ciclo198