Real-time image-content-based beamline control for smart 4D X-ray imaging

Vogelgesang, Matthias; Faragó, Tomáš; Morgeneyer, Thilo F.; Helfen, Lukas; Rolo, Tomy dos Santos; Myagotin, Anton; Baumbach, Tilo

doi:10.1107/s1600577516010195

Cited by 83 publications

(52 citation statements)

References 39 publications

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“…To perform quantitative analysis and 3D visualisation, phase retrieval was applied to reduce the edge enhancement and convert it to areal contrast. The UFO image processing framework (Vogelgesang et al ., 2016), an open‐source package (http://www.github.com/ufo-kit), was used to perform Paganin/TIE phase‐retrieval (Paganin et al ., 2002) on the projections and was followed by image reconstruction. For phase retrieval, the delta/beta ratio was fine‐tuned to the value of 500 to convert the edge enhancement.…”

Section: Methodsmentioning

confidence: 99%

High‐resolution imaging of the human incudostapedial joint using synchrotron‐radiation phase‐contrast imaging

Rohani

Allen

Gare

et al. 2020

Journal of Microscopy

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Summary The incudostapedial joint (ISJ) of the middle ear is important for proper transmission of sound energy to the cochlea. Recently, the biomechanics of the ISJ have been investigated using finite‐element (FE) modelling, using simplified geometry. The objective of the present study was to investigate the feasibility of synchrotron‐radiation phase‐contrast imaging (SR‐PCI) in visualising the ISJ ultrastructure. Three human cadaveric ISJs were dissected and scanned using SR‐PCI at 0.9 µm isotropic voxel size. One of the samples was previously scanned at 9 µm voxel size. The images were visually compared and contrast‐to‐noise ratios (CNRs) were calculated (of both bone and soft tissues) for quantitative comparisons. The ISJ ultrastructure as well as adjacent bone and soft tissues were clearly visible in images with a 0.9 µm voxel size. The CNRs of the 0.9 µm images were relatively lower than those of the 9 µm scans, while the ratio of bone to soft tissue CNRs were higher, indicating better discernibility of bone from soft tissue in the 0.9 µm scans. This study was the first known attempt to image the ISJ ultrastructure using an SR‐PCI scanner at submicron voxel size and results suggest that this method was successful. Future studies are needed to optimise the contrast and test the feasibility of imaging the ISJ in situ. Lay Description The human middle ear consists of the eardrum, three small bones (the malleus, incus and stapes) and two joints connecting the bones (the incudostapedial joint and the incudomallear joint). The role of the middle ear is to amplify and transfer sound energy to the cochlea, the end organ of hearing. The incudostapedial joint (ISJ) of the middle ear is a synovial joint which is important for proper transmission of sound energy to the cochlea. Similar to other synovial joints it consists of meniscus, fluid and articulating surfaces. Recently, the biomechanics of the ISJ have been investigated using computational models, using grossly simplified geometry. Synchrotron radiation phase contrast imaging (SR‐PCI) is a high‐resolution imaging technique used to visualise small structures in three dimensions. The objective of the present study was to investigate the feasibility of using SR‐PCI in visualising the ISJ ultrastructure. Three human cadaveric ISJs were dissected and scanned using SR‐PCI at 0.9 µm isotropic voxel size. One of the samples was previously scanned at 9 µm voxel size. The images were both qualitatively and quantitatively compared. This study was the first known attempt to image the ISJ ultrastructure using an SR‐PCI scanner at submicron voxel size and results suggest that this method was successful. Future studies are needed to optimise the contrast and feasibility of imaging the ISJ in situ.

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Section: Methodsmentioning

confidence: 99%

High‐resolution imaging of the human incudostapedial joint using synchrotron‐radiation phase‐contrast imaging

Rohani

Allen

Gare

et al. 2020

Journal of Microscopy

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“…The series of radiographs is then used to reconstruct 3D volumes via filtered-back projection [49]. A GPU-accelerated implementation of this algorithm [50] has been utilized herein. The reconstructed volume size is 1600 × 1600 × 1600 voxels (each voxel has a physical length of 1.1 µm).…”

Section: Methodsmentioning

confidence: 99%

Experimental-Numerical Validation Framework for Micromechanical Simulations

Buljac

Shakoor

Neggers

et al. 2017

Multiscale Modeling of Heterogeneous Structures

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A combined experimental-numerical framework is presented in order to validate computations at the microscale. It is illustrated for a flat specimen with two holes, which is made of cast iron and imaged via in situ synchrotron laminography at micrometer resolution during a tensile test. The region in the reconstructed volume between the two holes is analyzed via Digital Volume Correlation (DVC) to measure displacement fields. Finite Element (FE) simulations, whose mesh is made consistent with the studied material microstructure, are driven by measured Dirichlet boundary conditions. Damage levels and gray level residuals for DVC measurements and FE simulations are assessed for validation purposes.

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“…Unfortunately, such criteria exclude a lot of the most recently published candidates from use (Daurer et al, 2016;Prescher & Prakapenka, 2015;Vogelgesang et al, 2016;Liu et al, 2012). ISSN 1600-5775 One of the more likely recent candidates for such a tool is MMX-I (Bergamaschi et al, 2016).…”

Section: Big Data Processing: a Solution For Modern Scientific Data Pmentioning

confidence: 99%

Automatic processing of multimodal tomography datasets

Parsons

Price

Wadeson

et al. 2017

J Synchrotron Radiat

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With the development of fourth-generation high-brightness synchrotrons on the horizon, the already large volume of data that will be collected on imaging and mapping beamlines is set to increase by orders of magnitude. As such, an easy and accessible way of dealing with such large datasets as quickly as possible is required in order to be able to address the core scientific problems during the experimental data collection. Savu is an accessible and flexible big data processing framework that is able to deal with both the variety and the volume of data of multimodal and multidimensional scientific datasets output such as those from chemical tomography experiments on the I18 microfocus scanning beamline at Diamond Light Source.

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Real-time image-content-based beamline control for smart 4D X-ray imaging

Cited by 83 publications

References 39 publications

High‐resolution imaging of the human incudostapedial joint using synchrotron‐radiation phase‐contrast imaging

High‐resolution imaging of the human incudostapedial joint using synchrotron‐radiation phase‐contrast imaging

Experimental-Numerical Validation Framework for Micromechanical Simulations

Automatic processing of multimodal tomography datasets

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