Laminography as a tool for imaging large-size samples with high resolution.

Despite the increased brilliance of the new generation synchrotron sources, there is still a challenge with high-resolution scanning of very thick and absorbing samples, such as a whole mouse brain stained with heavy elements, and, extending further, brains of primates. Samples are typically cut into smaller parts, to ensure a sufficient X-ray transmission, and scanned separately. Compared with the standard tomography setup where the sample would be cut into many pillars, the laminographic geometry operates with slab-shaped sections significantly reducing the number of sample parts to be prepared, the cutting damage and data stitching problems. In this work, a laminography pipeline for imaging large samples (>1 cm) at micrometre resolution is presented. The implementation includes a low-cost instrument setup installed at the 2-BM micro-CT beamline of the Advanced Photon Source. Additionally, sample mounting, scanning techniques, data stitching procedures, a fast reconstruction algorithm with low computational complexity, and accelerated reconstruction on multi-GPU systems for processing large-scale datasets are presented. The applicability of the whole laminography pipeline was demonstrated by imaging four sequential slabs throughout an entire mouse brain sample stained with osmium, in total generating approximately 12 TB of raw data for reconstruction.

Real-time streaming tomographic reconstruction with on-demand data capturing and 3D zooming to regions of interest.

Complex dynamic tomographic experiments at brilliant X-ray light sources require real-time feedback on the sample changes with respect to environmental conditions, selecting representative regions of interest for high-resolution scanning, and on-demand data saving mechanisms for storing only relevant projections acquired by fast area detectors and reducing data volumes. Here the implementation details of a 3D real-time imaging monitoring instrument, with zooming to a volume of interest with easy-to-use visualization via ImageJ, a tool familiar to most beamline users, is presented. The instrument relies on optimized data flow between the detector and processing machines and is implemented on commodity computers. The instrument has been developed at beamline 2-BM of the Advanced Photon Source, where the automatic lens changing mechanism for zooming is implemented with an Optique Peter microscope. Performance tests demonstrate the ability to process more than 3 GB of projection data per second and generate real-time 3D zooming with different magnification. These new capabilities are essential for new APS Upgrade instruments such as the projection microscope under development at beamline 32-ID. The efficacy of the proposed instrument was demonstrated during an in situ tomographic experiment on ice and gas hydrate formation in porous samples.

Linking void and interphase evolution to electrochemistry in solid-state batteries using operando X-ray tomography.

Despite progress in solid-state battery engineering, our understanding of the chemo-mechanical phenomena that govern electrochemical behaviour and stability at solid-solid interfaces remains limited compared to at solid-liquid interfaces. Here, we use operando synchrotron X-ray computed microtomography to investigate the evolution of lithium/solid-state electrolyte interfaces during battery cycling, revealing how the complex interplay among void formation, interphase growth and volumetric changes determines cell behaviour. Void formation during lithium stripping is directly visualized in symmetric cells, and the loss of contact that drives current constriction at the interface between lithium and the solid-state electrolyte (Li10SnP2S12) is quantified and found to be the primary cause of cell failure. The interphase is found to be redox-active upon charge, and global volume changes occur owing to partial molar volume mismatches at either electrode. These results provide insight into how chemo-mechanical phenomena can affect cell performance, thus facilitating the development of solid-state batteries.

Improving reproducibility in synchrotron tomography using implementation-adapted filters.

For reconstructing large tomographic datasets fast, filtered backprojection-type or Fourier-based algorithms are still the method of choice, as they have been for decades. These robust and computationally efficient algorithms have been integrated in a broad range of software packages. The continuous mathematical formulas used for image reconstruction in such algorithms are unambiguous. However, variations in discretization and interpolation result in quantitative differences between reconstructed images, and corresponding segmentations, obtained from different software. This hinders reproducibility of experimental results, making it difficult to ensure that results and conclusions from experiments can be reproduced at different facilities or using different software. In this paper, a way to reduce such differences by optimizing the filter used in analytical algorithms is proposed. These filters can be computed using a wrapper routine around a black-box implementation of a reconstruction algorithm, and lead to quantitatively similar reconstructions. Use cases for this approach are demonstrated by computing implementation-adapted filters for several open-source implementations and applying them to simulated phantoms and real-world data acquired at the synchrotron. Our contribution to a reproducible reconstruction step forms a building block towards a fully reproducible synchrotron tomography data processing pipeline.

TomoGAN: low-dose synchrotron x-ray tomography with generative adversarial networks: discussion.

Synchrotron-based x-ray tomography is a noninvasive imaging technique that allows for reconstructing the internal structure of materials at high spatial resolutions from tens of micrometers to a few nanometers. In order to resolve sample features at smaller length scales, however, a higher radiation dose is required. Therefore, the limitation on the achievable resolution is set primarily by noise at these length scales. We present TomoGAN, a denoising technique based on generative adversarial networks, for improving the quality of reconstructed images for low-dose imaging conditions. We evaluate our approach in two photon-budget-limited experimental conditions: (1) sufficient number of low-dose projections (based on Nyquist sampling), and (2) insufficient or limited number of high-dose projections. In both cases, the angular sampling is assumed to be isotropic, and the photon budget throughout the experiment is fixed based on the maximum allowable radiation dose on the sample. Evaluation with both simulated and experimental datasets shows that our approach can significantly reduce noise in reconstructed images, improving the structural similarity score of simulation and experimental data from 0.18 to 0.9 and from 0.18 to 0.41, respectively. Furthermore, the quality of the reconstructed images with filtered back projection followed by our denoising approach exceeds that of reconstructions with the simultaneous iterative reconstruction technique, showing the computational superiority of our approach.

Nanoporous gold: a hierarchical and multiscale 3D test pattern for characterizing X-ray nano-tomography systems.

Full-field transmission X-ray microscopy (TXM) is a well established technique, available at various synchrotron beamlines around the world as well as by laboratory benchtop devices. One of the major TXM challenges, due to its nanometre-scale resolution, is the overall instrument stability during the acquisition of the series of tomographic projections. The ability to correct for vertical and horizontal distortions of each projection image during acquisition is necessary in order to achieve the effective 3D spatial resolution. The effectiveness of such an image alignment is also heavily influenced by the absorption properties and strong contrast of specific features in the scanned sample. Here it is shown that nanoporous gold (NPG) can be used as an ideal 3D test pattern for evaluating and optimizing the performance of a TXM instrument for hard X-rays at a synchrotron beamline. Unique features of NPG, such as hierarchical structures at multiple length scales and high absorbing capabilities, makes it an ideal choice for characterization, which involves a combination of a rapid-alignment algorithm applied on the acquired projections followed by the extraction of a set of both 2D- and 3D-descriptive image parameters. This protocol can be used for comparing the efficiency of TXM instruments at different synchrotron beamlines in the world or benchtop devices, based on a reference library of scanned NPG samples, containing information about the estimated horizontal and vertical alignment values, 2D qualitative parameters and quantitative 3D parameters. The possibility to tailor the ligament sizes of NPG to match the achievable resolution in combination with the high electron density of gold makes NPG an ideal 3D test pattern for evaluating the status and performance of a given synchrotron-based or benchtop-based TXM setup.

Xi-cam: a versatile interface for data visualization and analysis.

Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.

A convolutional neural network approach to calibrating the rotation axis for X-ray computed tomography.

This paper presents an algorithm to calibrate the center-of-rotation for X-ray tomography by using a machine learning approach, the Convolutional Neural Network (CNN). The algorithm shows excellent accuracy from the evaluation of synthetic data with various noise ratios. It is further validated with experimental data of four different shale samples measured at the Advanced Photon Source and at the Swiss Light Source. The results are as good as those determined by visual inspection and show better robustness than conventional methods. CNN has also great potential for reducing or removing other artifacts caused by instrument instability, detector non-linearity, etc. An open-source toolbox, which integrates the CNN methods described in this paper, is freely available through GitHub at tomography/xlearn and can be easily integrated into existing computational pipelines available at various synchrotron facilities. Source code, documentation and information on how to contribute are also provided.

Hard X-ray-induced damage on carbon-binder matrix for in situ synchrotron transmission X-ray microscopy tomography of Li-ion batteries.

The electrode of Li-ion batteries is required to be chemically and mechanically stable in the electrolyte environment for in situ monitoring by transmission X-ray microscopy (TXM). Evidence has shown that continuous irradiation has an impact on the microstructure and the electrochemical performance of the electrode. To identify the root cause of the radiation damage, a wire-shaped electrode is soaked in an electrolyte in a quartz capillary and monitored using TXM under hard X-ray illumination. The results show that expansion of the carbon-binder matrix by the accumulated X-ray dose is the key factor of radiation damage. For in situ TXM tomography, intermittent X-ray exposure during image capturing can be used to avoid the morphology change caused by radiation damage on the carbon-binder matrix.

Optimization of tomographic reconstruction workflows on geographically distributed resources.

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modeling of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Moreover, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks.

Integration of TomoPy and the ASTRA toolbox for advanced processing and reconstruction of tomographic synchrotron data.

The processing of tomographic synchrotron data requires advanced and efficient software to be able to produce accurate results in reasonable time. In this paper, the integration of two software toolboxes, TomoPy and the ASTRA toolbox, which, together, provide a powerful framework for processing tomographic data, is presented. The integration combines the advantages of both toolboxes, such as the user-friendliness and CPU-efficient methods of TomoPy and the flexibility and optimized GPU-based reconstruction methods of the ASTRA toolbox. It is shown that both toolboxes can be easily installed and used together, requiring only minor changes to existing TomoPy scripts. Furthermore, it is shown that the efficient GPU-based reconstruction methods of the ASTRA toolbox can significantly decrease the time needed to reconstruct large datasets, and that advanced reconstruction methods can improve reconstruction quality compared with TomoPy's standard reconstruction method.

Nanoscale Three-Dimensional Microstructural Characterization of an Sn-Rich Solder Alloy Using High-Resolution Transmission X-Ray Microscopy (TXM).

Three-dimensional (3D) nondestructive microstructural characterization was performed using full-field transmission X-ray microscopy on an Sn-rich alloy, at a spatial resolution of 60 nm. This study highlights the use of synchrotron radiation along with Fresnel zone plate optics to perform absorption contrast tomography for analyzing nanoscale features of fine second phase particles distributed in the tin matrix, which are representative of the bulk microstructure. The 3D reconstruction was also used to quantify microstructural details of the analyzed volume.

Hyperspectral image reconstruction for x-ray fluorescence tomography.

A penalized maximum-likelihood estimation is proposed to perform hyperspectral (spatio-spectral) image reconstruction for X-ray fluorescence tomography. The approach minimizes a Poisson-based negative log-likelihood of the observed photon counts, and uses a penalty term that has the effect of encouraging local continuity of model parameter estimates in both spatial and spectral dimensions simultaneously. The performance of the reconstruction method is demonstrated with experimental data acquired from a seed of arabidopsis thaliana collected at the 13-ID-E microprobe beamline at the Advanced Photon Source. The resulting element distribution estimates with the proposed approach show significantly better reconstruction quality than the conventional analytical inversion approaches, and allows for a high data compression factor which can reduce data acquisition times remarkably. In particular, this technique provides the capability to tomographically reconstruct full energy dispersive spectra without compromising reconstruction artifacts that impact the interpretation of results.

Dynamic intensity normalization using eigen flat fields in X-ray imaging.

In X-ray imaging, it is common practice to normalize the acquired projection data with averaged flat fields taken prior to the scan. Unfortunately, due to source instabilities, vibrating beamline components such as the monochromator, time varying detector properties, or other confounding factors, flat fields are often far from stationary, resulting in significant systematic errors in intensity normalization. In this work, a simple and efficient method is proposed to account for dynamically varying flat fields. Through principal component analysis of a set of flat fields, eigen flat fields are computed. A linear combination of the most important eigen flat fields is then used to individually normalize each X-ray projection. Experiments show that the proposed dynamic flat field correction leads to a substantial reduction of systematic errors in projection intensity normalization compared to conventional flat field correction.

3D vs 2D laparoscopic radical prostatectomy in organ-confined prostate cancer: comparison of operative data and pentafecta rates: a single cohort study.

BACKGROUND: Currently, men are younger at the time of diagnosis of prostate cancer and more interested in less invasive surgical approaches (traditional laparoscopy, 3D-laparoscopy, robotics). Outcomes of continence, erectile function, cancer cure, positive surgical margins and complication are well collected in the pentafecta rate. However, no comparative studies between 4th generation 3D-HD vision system laparoscopy and standard bi-dimensional laparoscopy have been reported. This study aimed to compare the operative, perioperative data and pentafecta rates between 2D and 3D laparoscopic radical prostatectomy (LRP) and to identify the actual role of 3D LRP in urology. METHODS: From October 2012 to July 2013, 86 patients with clinically localized prostate cancer [PCa: age ≤ 70 years, prostate-specific antigen (PSA) ≤ 10 ng/ml, biopsy Gleason score ≤ 7] underwent laparoscopic extraperitoneal radical prostatectomy (LERP) and were followed for approximately 14 months (range 12-25). Patients were selected for inclusion via hospital record data, and divided into two groups. Their patient records were then analyzed. Patients were randomized into two groups: the former 2D-LERP (43 pts) operated with the use of 2D-HD camera; the latter 3D-LERP (43 pts) operated with the use of a 3D-HD 4th generation view system. The operative and perioperative data and the pentafecta rates between 2D-LERP and 3D-LERP were compared. RESULTS: The overall pentafecta rates at 3 months were 47.4% and 49.6% in the 2D- and 3D-LERP group respectively. The pentafecta rate at 12 months was 62.7% and 67% for each group respectively. 4th generation 3D-HD vision system provides advantages over standard bi-dimensional view with regard to intraoperative steps. Our data suggest a trend of improvement in intraoperative blood loss and postoperative recovery of continence with the respect of the oncological safety. CONCLUSIONS: Use of the 3D technology by a single surgeon significantly enhances the possibility of achieving better intraoperative results and pentafecta in all patients undergoing LERP. Potency was the most difficult outcome to reach after surgery, and it was the main factor leading to pentafecta failure. Nevertheless, further studies are necessary to better comprehend the role of 3D-LERP in modern urology.

TomoPy: a framework for the analysis of synchrotron tomographic data.

Analysis of tomographic datasets at synchrotron light sources (including X-ray transmission tomography, X-ray fluorescence microscopy and X-ray diffraction tomography) is becoming progressively more challenging due to the increasing data acquisition rates that new technologies in X-ray sources and detectors enable. The next generation of synchrotron facilities that are currently under design or construction throughout the world will provide diffraction-limited X-ray sources and are expected to boost the current data rates by several orders of magnitude, stressing the need for the development and integration of efficient analysis tools. Here an attempt to provide a collaborative framework for the analysis of synchrotron tomographic data that has the potential to unify the effort of different facilities and beamlines performing similar tasks is described in detail. The proposed Python-based framework is open-source, platform- and data-format-independent, has multiprocessing capability and supports procedural programming that many researchers prefer. This collaborative platform could affect all major synchrotron facilities where new effort is now dedicated to developing new tools that can be deployed at the facility for real-time processing, as well as distributed to users for off-site data processing.

Scientific data exchange: a schema for HDF5-based storage of raw and analyzed data.

Data Exchange is a simple data model designed to interface, or `exchange', data among different instruments, and to enable sharing of data analysis tools. Data Exchange focuses on technique rather than instrument descriptions, and on provenance tracking of analysis steps and results. In this paper the successful application of the Data Exchange model to a variety of X-ray techniques, including tomography, fluorescence spectroscopy, fluorescence tomography and photon correlation spectroscopy, is described.

Retropubic, laparoscopic, and robot-assisted radical prostatectomy: surgical, oncological, and functional outcomes: a systematic review.

OBJECTIVES: Despite the wide diffusion of minimally invasive approaches, such as laparoscopic (LRP) and robot-assisted radical prostatectomy (RALP), few studies compare the results of these techniques with the retropubic radical prostatectomy (RRP) approach. The aim of this study is to compare the surgical, functional, and oncological outcomes and cost-effectiveness of RRP, LRP, and RALP. METHODS: A systematic review of the literature was performed in the PubMed and Embase databases in December 2013. A 'free-text' protocol using the term 'radical prostatectomy' was applied. A total of 16,085 records were found. The authors reviewed the records to identify comparative studies to include in the review. RESULTS: 44 comparative studies were identified. With regard to the perioperative outcome, LRP and RALP were more time-consuming than RRP, but blood loss, transfusion rates, catheterisation time, hospitalisation duration, and complication rates were the most optimal in the laparoscopic approaches. With regard to the functional and oncological results, RALP was found to have the best outcomes. CONCLUSION: Our study confirmed the well-known perioperative advantage of minimally invasive techniques; however, available data were not sufficient to prove the superiority of any surgical approach in terms of functional and oncologic outcomes. On the contrary, cost comparison clearly supports RRP.

Localised prostate cancer and hemophilia A (AHA): Case report and management of the disease.

Acquired Hemophilia A (AHA) is a rare bleeding diathesis characterized by the development of autoantibodies against factor VIII (FVIII). About half of the cases are idiopathic and the other half are associated with autoimmune diseases, postpartum problems, infections, inflammatory bowel disease, drugs, lymphoproliferative disorders or solid tumors . AHA is associated with malignancies in 7-15% of cases. We report a case of AHA in a 65 year old patient with prostatic carcinoma, who underwent retropubic radical prostatectomy (RP).

A comparative study of X-ray tomographic microscopy on shales at different synchrotron facilities: ALS, APS and SLS.

Synchrotron radiation X-ray tomographic microscopy (SRXTM) was used to characterize the three-dimensional microstructure, geometry and distribution of different phases in two shale samples obtained from the North Sea (sample N1) and the Upper Barnett Formation in Texas (sample B1). Shale is a challenging material because of its multiphase composition, small grain size, low but significant amount of porosity, as well as strong shape- and lattice-preferred orientation. The goals of this round-robin project were to (i) characterize microstructures and porosity on the micrometer scale, (ii) compare results measured at three synchrotron facilities, and (iii) identify optimal experimental conditions of high-resolution SRXTM for fine-grained materials. SRXTM data of these shales were acquired under similar conditions at the Advanced Light Source (ALS) of Lawrence Berkeley National Laboratory, USA, the Advanced Photon Source (APS) of Argonne National Laboratory, USA, and the Swiss Light Source (SLS) of the Paul Scherrer Institut, Switzerland. The data reconstruction of all datasets was handled under the same procedures in order to compare the data quality and determine phase proportions and microstructures. With a 10× objective lens the spatial resolution is approximately 2 µm. The sharpness of phase boundaries in the reconstructed data collected from the APS and SLS was comparable and slightly more refined than in the data obtained from the ALS. Important internal features, such as pyrite (high-absorbing), and low-density features, including pores, fractures and organic matter or kerogen (low-absorbing), were adequately segmented on the same basis. The average volume fractions of low-density features for sample N1 and B1 were estimated at 6.3 (6)% and 4.5 (4)%, while those of pyrite were calculated to be 5.6 (6)% and 2.0 (3)%, respectively. The discrepancy of data quality and volume fractions were mainly due to different types of optical instruments and varying technical set-ups at the ALS, APS and SLS.