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Disney CM, Vo NT, Bodey AJ, Bay BK, Lee PD. Image quality and scan time optimisation for in situ phase contrast x-ray tomography of the intervertebral disc. J Mech Behav Biomed Mater 2023; 138:105579. [PMID: 36463809 DOI: 10.1016/j.jmbbm.2022.105579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 11/14/2022] [Accepted: 11/16/2022] [Indexed: 11/20/2022]
Abstract
In-line phase contrast synchrotron tomography combined with in situ mechanical loading enables the characterisation of soft tissue micromechanics via digital volume correlation (DVC) within whole organs. Optimising scan time is important for reducing radiation dose from multiple scans and to limit sample movement during acquisition. Also, although contrasted edges provided by in-line phase contrast tomography of soft tissues are useful for DVC, the effect of phase contrast imaging on its accuracy has yet to be investigated. Due to limited time at synchrotron facilities, scan parameters are often decided during imaging and their effect on DVC accuracy is not fully understood. Here, we used previously published data of intervertebral disc phase contrast tomography to evaluate the influence of i) fibrous image texture, ii) number of projections, iii) tomographic reconstruction method, and iv) phase contrast propagation distance on DVC results. A greater understanding of how image texture influences optimal DVC tracking was obtained by visualising objective function mapping, enabling tracking inaccuracies to be identified. When reducing the number of projections, DVC was minimally affected by image high frequency noise but with a compromise in accuracy. Iterative reconstruction methods improved image signal-to-noise and consequently significantly lowered DVC displacement uncertainty. Propagation distance was shown to affect DVC accuracy. Consistent DVC results were achieved within a propagation distance range which provided contrast to the smallest scale features, where; too short a distance provided insufficient features to track, whereas too long led to edge effect inconsistencies, particularly at greater deformations. Although limited to a single sample type and image setup, this study provides general guidelines for future investigations when optimising image quality and scan times for in situ phase contrast x-ray tomography of fibrous connective tissues.
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Affiliation(s)
- C M Disney
- Mechanical Engineering, University College London, UK; Diamond Light Source, UK.
| | - N T Vo
- Diamond Light Source, UK; National Synchrotron Light Source II, Brookhaven National Laboratory, USA
| | | | - B K Bay
- School of Mechanical, Industrial & Manufacturing Engineering, Oregon State University, USA
| | - P D Lee
- Mechanical Engineering, University College London, UK
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2
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Levine ZH, Garboczi EJ, Peskin AP, Ekman AA, Mansfield E, Holm JD. X-ray computed tomography using partially coherent Fresnel diffraction with application to an optical fiber. OPTICS EXPRESS 2021; 29:1788-1804. [PMID: 33726385 PMCID: PMC7920526 DOI: 10.1364/oe.414398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 12/18/2020] [Accepted: 12/21/2020] [Indexed: 05/17/2023]
Abstract
A reconstruction algorithm for partially coherent x-ray computed tomography (XCT) including Fresnel diffraction is developed and applied to an optical fiber. The algorithm is applicable to a high-resolution tube-based laboratory-scale x-ray tomography instrument. The computing time is only a few times longer than the projective counterpart. The algorithm is used to reconstruct, with projections and diffraction, a tilt series acquired at the micrometer scale of a graded-index optical fiber using maximum likelihood and a Bayesian method based on the work of Bouman and Sauer. The inclusion of Fresnel diffraction removes some reconstruction artifacts and use of a Bayesian prior probability distribution removes others, resulting in a substantially more accurate reconstruction.
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Affiliation(s)
- Zachary H. Levine
- Quantum Metrology Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA
| | - Edward J. Garboczi
- Applied Chemicals and Materials Division, National Institute of Standards and Technology, Boulder, CO 80305, USA
| | - Adele P. Peskin
- Software and Systems Division, National Institute of Standards and Technology, Boulder, CO 80305, USA
| | - Axel A. Ekman
- Department of Anatomy, University of California San Francisco, San Francisco, CA 94158, USA
| | - Elisabeth Mansfield
- Applied Chemicals and Materials Division, National Institute of Standards and Technology, Boulder, CO 80305, USA
| | - Jason D. Holm
- Applied Chemicals and Materials Division, National Institute of Standards and Technology, Boulder, CO 80305, USA
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3
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Schaff F, Morgan KS, Pollock JA, Croton LCP, Hooper SB, Kitchen MJ. Material Decomposition Using Spectral Propagation-Based Phase-Contrast X-Ray Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:3891-3899. [PMID: 32746132 DOI: 10.1109/tmi.2020.3006815] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Material decomposition in X-ray imaging uses the energy-dependence of attenuation to digitally decompose an object into specific constituent materials, generally at the cost of enhanced image noise. Propagation-based X-ray phase-contrast imaging is a developing technique that can be used to reduce image noise, in particular from weakly attenuating objects. In this paper, we combine spectral phase-contrast imaging with material decomposition to both better visualize weakly attenuating features and separate them from overlying objects in radiography. We derive an algorithm that performs both tasks simultaneously and verify it against numerical simulations and experimental measurements of ideal two-component samples composed of pure aluminum and poly(methyl methacrylate). Additionally, we showcase first imaging results of a rabbit kitten's lung. The attenuation signal of a thorax, in particular, is dominated by the strongly attenuating bones of the ribcage. Combined with the weak soft tissue signal, this makes it difficult to visualize the fine anatomical structures across the whole lung. In all cases, clean material decomposition was achieved, without residual phase-contrast effects, from which we generate an un-obstructed image of the lung, free of bones. Spectral propagation-based phase-contrast imaging has the potential to be a valuable tool, not only in future lung research, but also in other systems for which phase-contrast imaging in combination with material decomposition proves to be advantageous.
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Chattopadhyay B, Madathiparambil AS, Mürer FK, Cerasi P, Chushkin Y, Zontone F, Gibaud A, Breiby DW. Nanoscale imaging of shale fragments with coherent X-ray diffraction. J Appl Crystallogr 2020; 53:1562-1569. [PMID: 33304225 PMCID: PMC7710485 DOI: 10.1107/s1600576720013850] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Accepted: 10/17/2020] [Indexed: 11/10/2022] Open
Abstract
Despite the abundance of shales in the Earth's crust and their industrial and environmental importance, their microscale physical properties are poorly understood, owing to the presence of many structurally related mineral phases and a porous network structure spanning several length scales. Here, the use of coherent X-ray diffraction imaging (CXDI) to study the internal structure of microscopic shale fragments is demonstrated. Simultaneous wide-angle X-ray diffraction (WAXD) measurement facilitated the study of the mineralogy of the shale microparticles. It was possible to identify pyrite nanocrystals as inclusions in the quartz-clay matrix and the volume of closed unconnected pores was estimated. The combined CXDI-WAXD analysis enabled the establishment of a correlation between sample morphology and crystallite shape and size. The results highlight the potential of the combined CXDI-WAXD approach as an upcoming imaging modality for 3D nanoscale studies of shales and other geological formations via serial measurements of microscopic fragments.
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Affiliation(s)
- Basab Chattopadhyay
- PoreLab, Department of Physics, Norwegian University of Science and Technology (NTNU), Høgskoleringen 5, Trondheim, 7491, Norway
| | - Aldritt S Madathiparambil
- PoreLab, Department of Physics, Norwegian University of Science and Technology (NTNU), Høgskoleringen 5, Trondheim, 7491, Norway
| | - Fredrik K Mürer
- PoreLab, Department of Physics, Norwegian University of Science and Technology (NTNU), Høgskoleringen 5, Trondheim, 7491, Norway
| | - Pierre Cerasi
- Petroleum Department, SINTEF Industry, Trondheim, 7465, Norway
| | - Yuriy Chushkin
- ESRF - The European Synchrotron, 71 Avenue des Martyrs, Grenoble, 38000, France
| | - Federico Zontone
- ESRF - The European Synchrotron, 71 Avenue des Martyrs, Grenoble, 38000, France
| | - Alain Gibaud
- LUNAM, IMMM, UMR 6283 CNRS, Faculté des Sciences, Le Mans, 72085, France
| | - Dag W Breiby
- PoreLab, Department of Physics, Norwegian University of Science and Technology (NTNU), Høgskoleringen 5, Trondheim, 7491, Norway.,Department of Microsystems, University of South-Eastern Norway, Campus Vestfold, Borre, 3182, Norway
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Hehn L, Gradl R, Dierolf M, Morgan KS, Paganin DM, Pfeiffer F. Model-Based Iterative Reconstruction for Propagation-Based Phase-Contrast X-Ray CT including Models for the Source and the Detector. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:1975-1987. [PMID: 31880549 DOI: 10.1109/tmi.2019.2962615] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Propagation-based phase-contrast X-ray computed tomography is a valuable tool for high-resolution visualization of biological samples, giving distinct improvements in terms of contrast and dose requirements compared to conventional attenuation-based computed tomography. Due to its ease of implementation and advances in laboratory X-ray sources, this imaging technique is increasingly being transferred from synchrotron facilities to laboratory environments. This however poses additional challenges, such as the limited spatial coherence and flux of laboratory sources, resulting in worse resolution and higher noise levels. Here we extend a previously developed iterative reconstruction algorithm for this imaging technique to include models for the reduced spatial coherence and the signal spreading of efficient scintillator-based detectors directly into the physical forward model. Furthermore, we employ a noise model which accounts for the full covariance statistics of the image formation process. In addition, we extend the model describing the interference effects such that it now matches the formalism of the widely-used single-material phase-retrieval algorithm, which is based on the sample-homogeneity assumption. We perform a simulation study as well as an experimental study at a laboratory inverse Compton source and compare our approach to the conventional analytical approaches. We find that the modeling of the source and the detector inside the physical forward model can tremendously improve the resolution at matched noise levels and that the modeling of the covariance statistics reduces overshoots (i.e. incorrect increase / decrease in sample properties) at the sample edges significantly.
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Bukreeva I, Asadchikov V, Buzmakov A, Chukalina M, Ingacheva A, Korolev NA, Bravin A, Mittone A, Biella GEM, Sierra A, Brun F, Massimi L, Fratini M, Cedola A. High resolution 3D visualization of the spinal cord in a post-mortem murine model. BIOMEDICAL OPTICS EXPRESS 2020; 11:2235-2253. [PMID: 32341880 PMCID: PMC7173906 DOI: 10.1364/boe.386837] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Revised: 02/27/2020] [Accepted: 03/02/2020] [Indexed: 05/04/2023]
Abstract
A crucial issue in the development of therapies to treat pathologies of the central nervous system is represented by the availability of non-invasive methods to study the three-dimensional morphology of spinal cord, with a resolution able to characterize its complex vascular and neuronal organization. X-ray phase contrast micro-tomography enables a high-quality, 3D visualization of both the vascular and neuronal network simultaneously without the need of contrast agents, destructive sample preparations or sectioning. Until now, high resolution investigations of the post-mortem spinal cord in murine models have mostly been performed in spinal cords removed from the spinal canal. We present here post-mortem phase contrast micro-tomography images reconstructed using advanced computational tools to obtain high-resolution and high-contrast 3D images of the fixed spinal cord without removing the bones and preserving the richness of micro-details available when measuring exposed spinal cords. We believe that it represents a significant step toward the in-vivo application.
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Affiliation(s)
- Inna Bukreeva
- Institute of Nanotechnology- CNR, Rome Unit, Piazzale Aldo Moro 5, Italy
- P. N. Lebedev Physical Institute, RAS, Leninsky pr., 53, Moscow, Russia
| | - Victor Asadchikov
- Shubnikov Institute of Crystallography FSRC “Crystallography and Photonics” RAS, Leninsky prosp., 59, Moscow, Russia
| | - Alexey Buzmakov
- Shubnikov Institute of Crystallography FSRC “Crystallography and Photonics” RAS, Leninsky prosp., 59, Moscow, Russia
| | - Marina Chukalina
- Shubnikov Institute of Crystallography FSRC “Crystallography and Photonics” RAS, Leninsky prosp., 59, Moscow, Russia
- Intitute for Information Transmission Problems RAS, Bolshoi Karetny per, 9, Moscow, Russia
| | - Anastasya Ingacheva
- Intitute for Information Transmission Problems RAS, Bolshoi Karetny per, 9, Moscow, Russia
| | - Nikolay A. Korolev
- National Research Nuclear University /Moscow Engineering Physics Institute, Kashirskoye Highway, 31 Moscow, Russia
| | - Alberto Bravin
- European Synchrotron Radiation Facility, 71 Avenue des Martyrs, Grenoble, France
| | - Alberto Mittone
- CELLS - ALBA Synchrotron Light Source, Carrer de la Llum, 2-26, Cerdanyola del Valles, Barcelona, Spain
| | | | - Alejandra Sierra
- Biomedical Imaging Unit, A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Francesco Brun
- Department of Engineering and Architecture, University of Trieste, Via A. Valerio, 6/1 Trieste, Italy
| | - Lorenzo Massimi
- Department of Medical Physics and Biomedical Engineering, University College London, Gower Street, London, WC1E 6BT, United Kingdom
| | - Michela Fratini
- Institute of Nanotechnology- CNR, Rome Unit, Piazzale Aldo Moro 5, Italy
- Fondazione Santa Lucia I.R.C.C.S., Via Ardeatina 306, Roma, Italy
| | - Alessia Cedola
- Institute of Nanotechnology- CNR, Rome Unit, Piazzale Aldo Moro 5, Italy
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7
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Allner S, Gustschin A, Fehringer A, Noël PB, Pfeiffer F. Metric-guided regularisation parameter selection for statistical iterative reconstruction in computed tomography. Sci Rep 2019; 9:6016. [PMID: 30979911 PMCID: PMC6461679 DOI: 10.1038/s41598-019-40837-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Accepted: 02/18/2019] [Indexed: 11/09/2022] Open
Abstract
As iterative reconstruction in Computed Tomography (CT) is an ill-posed problem, additional prior information has to be used to get a physically meaningful result (close to ground truth if available). However, the amount of influence of the regularisation prior is crucial to the outcome of the reconstruction. Therefore, we propose a scheme for tuning the strength of the prior via a certain image metric. In this work, the parameter is tuned for minimal histogram entropy in selected regions of the reconstruction as histogram entropy is a very basic approach to characterise the information content of data. We performed a sweep over different regularisation parameters showing that the histogram entropy is a suitable metric as it is well behaved over a wide range of parameters. The parameter determination is a feedback loop approach we applied to numerically simulated FORBILD phantom data and verified with an experimental measurement of a micro-CT device. The outcome is evaluated visually and quantitatively by means of root mean squared error (RMSE) and structural similarity (SSIM) for the simulation and visually for the measured sample (no ground truth available). The final reconstructed images exhibit noise-suppressed iterative reconstruction. For both datasets, the optimisation is robust where its initial value is concerned. The parameter tuning approach shows that the proposed metric-driven feedback loop is a promising tool for finding a suitable regularisation parameter in statistical iterative reconstruction.
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Affiliation(s)
- Sebastian Allner
- Chair of Biomedical Physics and Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748, Garching, Germany.
| | - Alex Gustschin
- Chair of Biomedical Physics and Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748, Garching, Germany
| | | | - Peter B Noël
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, 81675, München, Germany
| | - Franz Pfeiffer
- Chair of Biomedical Physics and Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748, Garching, Germany
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, 81675, München, Germany
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8
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Gross V, Müller M, Hehn L, Ferstl S, Allner S, Dierolf M, Achterhold K, Mayer G, Pfeiffer F. X-ray imaging of a water bear offers a new look at tardigrade internal anatomy. ZOOLOGICAL LETTERS 2019; 5:14. [PMID: 31110777 PMCID: PMC6511223 DOI: 10.1186/s40851-019-0130-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Accepted: 04/09/2019] [Indexed: 05/03/2023]
Abstract
BACKGROUND Tardigrades (water bears) are microscopic invertebrates of which the anatomy has been well studied using traditional techniques, but a comprehensive three-dimensional reconstruction has never been performed. In order to close this gap, we employed X-ray computed tomography (CT), a technique that is becoming increasingly popular in zoology for producing high-resolution, three-dimensional (3D) scans of whole specimens. While CT has long been used to scan larger samples, its use in some microscopic animals can be problematic, as they are often too small for conventional CT yet too large for high-resolution, optics-based soft X-ray microscopy. This size gap continues to be narrowed with advancements in technology, with high-resolution imaging now being possible using both large synchrotron devices and, more recently, laboratory-based instruments. RESULTS Here we use a recently developed prototype lab-based nano-computed tomography device to image a 152 μm-long tardigrade at high resolution (200-270 nm pixel size). The resulting dataset allowed us to visualize the anatomy of the tardigrade in 3D and analyze the spatial relationships of the internal structures. Segmentation of the major structures of the body enabled the direct measurement of their respective volumes. Furthermore, we segmented every storage cell individually and quantified their volume distribution. We compare our measurements to those from published studies in which other techniques were used. CONCLUSIONS The data presented herein demonstrate the utility of CT imaging as a powerful supplementary tool for studies of tardigrade anatomy, especially for quantitative volume measurements. This nanoCT study represents the smallest complete animal ever imaged using CT, and offers new 3D insights into the spatial relationships of the internal organs of water bears.
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Affiliation(s)
- Vladimir Gross
- Department of Zoology, Institute of Biology, University of Kassel, Heinrich-Plett-Straße 40, 34132 Kassel, Germany
| | - Mark Müller
- Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching, Germany
| | - Lorenz Hehn
- Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching, Germany
| | - Simone Ferstl
- Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching, Germany
| | - Sebastian Allner
- Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching, Germany
| | - Martin Dierolf
- Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching, Germany
| | - Klaus Achterhold
- Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching, Germany
| | - Georg Mayer
- Department of Zoology, Institute of Biology, University of Kassel, Heinrich-Plett-Straße 40, 34132 Kassel, Germany
| | - Franz Pfeiffer
- Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching, Germany
- Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany
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9
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Hehn L, Gradl R, Voss A, Günther B, Dierolf M, Jud C, Willer K, Allner S, Hammel JU, Hessler R, Morgan KS, Herzen J, Hemmert W, Pfeiffer F. Propagation-based phase-contrast tomography of a guinea pig inner ear with cochlear implant using a model-based iterative reconstruction algorithm. BIOMEDICAL OPTICS EXPRESS 2018; 9:5330-5339. [PMID: 30460131 PMCID: PMC6238946 DOI: 10.1364/boe.9.005330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 08/17/2018] [Accepted: 09/08/2018] [Indexed: 06/09/2023]
Abstract
Propagation-based phase-contrast computed tomography has become a valuable tool for visualization of three-dimensional biological samples, due to its high contrast between materials with similar attenuation properties. However, one of the most-widely used phase-retrieval algorithms imposes a homogeneity assumption onto the sample, which leads to artifacts for numerous applications where this assumption is violated. Prominent examples are biological samples with highly-absorbing implants. Using synchrotron radiation, we demonstrate by the example of a guinea pig inner ear with a cochlear implant electrode, how a recently developed model-based iterative algorithm for propagation-based phase-contrast computed tomography yields distinct benefits for such a task. We find that the model-based approach improves the overall image quality, removes the detrimental influence of the implant and accurately visualizes the cochlea.
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Affiliation(s)
- Lorenz Hehn
- Chair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching,
Germany
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts der Isar, Technical University of Munich, 81675 Munich,
Germany
| | - Regine Gradl
- Chair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching,
Germany
- Institute for Advanced Study, Technical University of Munich, 85748 Garching,
Germany
| | - Andrej Voss
- Bio-Inspired Information Processing, Munich School of BioEngineering, Munich School of Robotics and Machine Intelligence, Technical University of Munich, 85748 Garching,
Germany
| | - Benedikt Günther
- Chair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching,
Germany
- Max-Planck-Institute of Quantum Optics, 85748 Garching,
Germany
| | - Martin Dierolf
- Chair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching,
Germany
| | - Christoph Jud
- Chair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching,
Germany
| | - Konstantin Willer
- Chair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching,
Germany
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts der Isar, Technical University of Munich, 81675 Munich,
Germany
| | - Sebastian Allner
- Chair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching,
Germany
| | - Jörg U. Hammel
- Institute of Materials Research, Helmholtz-Zentrum Geesthacht, 21502 Geesthacht,
Germany
- Institut für Zoologie und Evolutionsforschung mit Phyletischem Museum, Ernst-Haeckel-Haus und Biologiedidaktik, Friedrich-Schiller-Universität Jena, 07743 Jena,
Germany
| | | | - Kaye S. Morgan
- Chair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching,
Germany
- Institute for Advanced Study, Technical University of Munich, 85748 Garching,
Germany
- School of Physics and Astronomy, Monash University, Clayton VIC 3800,
Australia
| | - Julia Herzen
- Chair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching,
Germany
| | - Werner Hemmert
- Bio-Inspired Information Processing, Munich School of BioEngineering, Munich School of Robotics and Machine Intelligence, Technical University of Munich, 85748 Garching,
Germany
| | - Franz Pfeiffer
- Chair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, 85748 Garching,
Germany
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts der Isar, Technical University of Munich, 81675 Munich,
Germany
- Institute for Advanced Study, Technical University of Munich, 85748 Garching,
Germany
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