TY - JOUR A1 - Hoerth, Rebecca M. A1 - Baum, Daniel A1 - Knötel, David A1 - Prohaska, Steffen A1 - Willie, Bettina M. A1 - Duda, Georg A1 - Hege, Hans-Christian A1 - Fratzl, Peter A1 - Wagermaier, Wolfgang T1 - Registering 2D and 3D Imaging Data of Bone during Healing JF - Connective Tissue Research Y1 - 2015 U6 - https://doi.org/10.3109/03008207.2015.1005210 VL - 56 IS - 2 SP - 133 EP - 143 PB - Taylor & Francis ER - TY - GEN A1 - Weber, Britta A1 - Tranfield, Erin M. A1 - Höög, Johanna L. A1 - Baum, Daniel A1 - Antony, Claude A1 - Hyman, Tony A1 - Verbavatz, Jean-Marc A1 - Prohaska, Steffen T1 - Automated stitching of microtubule centerlines across serial electron tomograms N2 - Tracing microtubule centerlines in serial section electron tomography requires microtubules to be stitched across sections, that is lines from different sections need to be aligned, endpoints need to be matched at section boundaries to establish a correspondence between neighboring sections, and corresponding lines need to be connected across multiple sections. We present computational methods for these tasks: 1) An initial alignment is computed using a distance compatibility graph. 2) A fine alignment is then computed with a probabilistic variant of the iterative closest points algorithm, which we extended to handle the orientation of lines by introducing a periodic random variable to the probabilistic formulation. 3) Endpoint correspondence is established by formulating a matching problem in terms of a Markov random field and computing the best matching with belief propagation. Belief propagation is not generally guaranteed to converge to a minimum. We show how convergence can be achieved, nonetheless, with minimal manual input. In addition to stitching microtubule centerlines, the correspondence is also applied to transform and merge the electron tomograms. We applied the proposed methods to samples from the mitotic spindle in C. elegans, the meiotic spindle in X. laevis, and sub-pellicular microtubule arrays in T. brucei. The methods were able to stitch microtubules across section boundaries in good agreement with experts’ opinions for the spindle samples. Results, however, were not satisfactory for the microtubule arrays. For certain experiments, such as an analysis of the spindle, the proposed methods can replace manual expert tracing and thus enable the analysis of microtubules over long distances with reasonable manual effort. T3 - ZIB-Report - 14-41 KW - electron tomography KW - microtubules KW - serial sectioning KW - image analysis KW - geometry reconstruction KW - image and geometry alignment KW - point correspondence Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-52958 SN - 1438-0064 ER - TY - GEN A1 - Kaplan, Bernhard A1 - Laufer, Jan A1 - Prohaska, Steffen A1 - Buchmann, Jens T1 - Monte-Carlo-based inversion scheme for 3D quantitative photoacoustic tomography N2 - The goal of quantitative photoacoustic tomography (qPAT) is to recover maps of the chromophore distributions from multiwavelength images of the initial pressure. Model-based inversions that incorporate the physical processes underlying the photoacoustic (PA) signal generation represent a promising approach. Monte-Carlo models of the light transport are computationally expensive, but provide accurate fluence distributions predictions, especially in the ballistic and quasi-ballistic regimes. Here, we focus on the inverse problem of 3D qPAT of blood oxygenation and investigate the application of the Monte-Carlo method in a model-based inversion scheme. A forward model of the light transport based on the MCX simulator and acoustic propagation modeled by the k-Wave toolbox was used to generate a PA image data set acquired in a tissue phantom over a planar detection geometry. The combination of the optical and acoustic models is shown to account for limited-view artifacts. In addition, the errors in the fluence due to, for example, partial volume artifacts and absorbers immediately adjacent to the region of interest are investigated. To accomplish large-scale inversions in 3D, the number of degrees of freedom is reduced by applying image segmentation to the initial pressure distribution to extract a limited number of regions with homogeneous optical parameters. The absorber concentration in the tissue phantom was estimated using a coordinate descent parameter search based on the comparison between measured and modeled PA spectra. The estimated relative concentrations using this approach lie within 5 % compared to the known concentrations. Finally, we discuss the feasibility of this approach to recover the blood oxygenation from experimental data. T3 - ZIB-Report - 17-04 KW - quantitative photoacoustic tomography KW - model-based inversion KW - oxygen saturation KW - chromophore concentration KW - photoacoustic imaging KW - Monte Carlo methods for light transport KW - boundary conditions KW - coordinate search Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-62318 SN - 1438-0064 ER - TY - CHAP A1 - Kaplan, Bernhard A1 - Buchmann, Jens A1 - Prohaska, Steffen A1 - Laufer, Jan T1 - Monte-Carlo-based inversion scheme for 3D quantitative photoacoustic tomography T2 - Proc. of SPIE, Photons Plus Ultrasound: Imaging and Sensing 2017 N2 - The goal of quantitative photoacoustic tomography (qPAT) is to recover maps of the chromophore distributions from multiwavelength images of the initial pressure. Model-based inversions that incorporate the physical processes underlying the photoacoustic (PA) signal generation represent a promising approach. Monte-Carlo models of the light transport are computationally expensive, but provide accurate fluence distributions predictions, especially in the ballistic and quasi-ballistic regimes. Here, we focus on the inverse problem of 3D qPAT of blood oxygenation and investigate the application of the Monte-Carlo method in a model-based inversion scheme. A forward model of the light transport based on the MCX simulator and acoustic propagation modeled by the k-Wave toolbox was used to generate a PA image data set acquired in a tissue phantom over a planar detection geometry. The combination of the optical and acoustic models is shown to account for limited-view artifacts. In addition, the errors in the fluence due to, for example, partial volume artifacts and absorbers immediately adjacent to the region of interest are investigated. To accomplish large-scale inversions in 3D, the number of degrees of freedom is reduced by applying image segmentation to the initial pressure distribution to extract a limited number of regions with homogeneous optical parameters. The absorber concentration in the tissue phantom was estimated using a coordinate descent parameter search based on the comparison between measured and modeled PA spectra. The estimated relative concentrations using this approach lie within 5 % compared to the known concentrations. Finally, we discuss the feasibility of this approach to recover the blood oxygenation from experimental data. Y1 - 2017 U6 - https://doi.org/10.1117/12.2251945 VL - 10064 SP - 100645J EP - 100645J-13 ER - TY - CHAP A1 - Buchmann, Jens A1 - Kaplan, Bernhard A1 - Prohaska, Steffen A1 - Laufer, Jan T1 - Experimental validation of a Monte-Carlo-based inversion scheme for 3D quantitative photoacoustic tomography T2 - Proc. of SPIE, Photons Plus Ultrasound: Imaging and Sensing N2 - Quantitative photoacoustic tomography (qPAT) aims to extract physiological parameters, such as blood oxygen saturation (sO2), from measured multi-wavelength image data sets. The challenge of this approach lies in the inherently nonlinear fluence distribution in the tissue, which has to be accounted for by using an appropriate model, and the large scale of the inverse problem. In addition, the accuracy of experimental and scanner-specific parameters, such as the wavelength dependence of the incident fluence, the acoustic detector response, the beam profile and divergence, needs to be considered. This study aims at quantitative imaging of blood sO2, as it has been shown to be a more robust parameter compared to absolute concentrations. We propose a Monte-Carlo–based inversion scheme in conjunction with a reduction in the number of variables achieved using image segmentation. The inversion scheme is experimentally validated in tissue-mimicking phantoms consisting of polymer tubes suspended in a scattering liquid. The tubes were filled with chromophore solutions at different concentration ratios. 3-D multi-spectral image data sets were acquired using a Fabry-Perot based PA scanner. A quantitative comparison of the measured data with the output of the forward model is presented. Parameter estimates of chromophore concentration ratios were found to be within 5 % of the true values. Y1 - 2017 U6 - https://doi.org/10.1117/12.2252359 VL - 10064 SP - 1006416 EP - 1006416-8 ER - TY - GEN A1 - Zhukova, Yulia A1 - Hiepen, Christian A1 - Knaus, Petra A1 - Osterland, Marc A1 - Prohaska, Steffen A1 - Dunlop, John W. C. A1 - Fratzl, Peter A1 - Skorb, Ekaterina V. T1 - The role of titanium surface nanotopography on preosteoblast morphology, adhesion and migration N2 - Surface structuring of titanium-based implants with appropriate nanotopographies can significantly modulate their impact on the biological behavior of cells populating these implants. Implant assisted bone tissue repair and regeneration require functional adhesion and expansion of bone progenitors. The surface nanotopography of implant materials used to support bone healing and its effect on cell behavior, in particular cell adhesion, spreading, expansion, and motility, is still not clearly understood. The aim of this study is to investigate preosteoblast proliferation, adhesion, morphology, and migration on different titanium materials with similar surface chemistry, but distinct nanotopographical features. Sonochemical treatment and anodic oxidation were employed to fabricate disordered – mesoporous titania (TMS), and ordered – titania nanotubular (TNT) topographies respectively. The morphological evaluation revealed a surface dependent shape, thickness, and spreading of cells owing to different adherence behavior. Cells were polygonal-shaped and well-spread on glass and TMS, but displayed an elongated fibroblast-like morphology on TNT surfaces. The cells on glass however, were much flatter than on nanostructured surfaces. Both nanostructured surfaces impaired cell adhesion, but TMS was more favorable for cell growth due to its support of cell attachment and spreading in contrast to TNT. Quantitative wound healing assay in combination with live-cell imaging revealed that cells seeded on TMS surfaces migrated in close proximity to neighboring cells and less directed when compared to the migratory behavior on other surfaces. The results indicate distinctly different cell adhesion and migration on ordered and disordered titania nanotopographies, providing important information that could be used in optimizing titanium-based scaffold design to foster bone tissue growth and repair. T3 - ZIB-Report - 17-06 Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-63053 SN - 1438-0064 ER - TY - JOUR A1 - Homberg, Ulrike A1 - Baum, Daniel A1 - Prohaska, Steffen A1 - Günster, Jens A1 - Krauß-Schüler, Stefanie T1 - Adapting trabecular structures for 3D printing: an image processing approach based on µCT data JF - Biomedical Physics & Engineering Express N2 - Materials with a trabecular structure notably combine advantages such as lightweight, reasonable strength, and permeability for fluids. This combination of advantages is especially interesting for tissue engineering in trauma surgery and orthopedics. Bone-substituting scaffolds for instance are designed with a trabecular structure in order to allow cell migration for bone ingrowth and vascularization. An emerging and recently very popular technology to produce such complex, porous structures is 3D printing. However, several technological aspects regarding the scaffold architecture, the printable resolution, and the feature size have to be considered when fabricating scaffolds for bone tissue replacement and regeneration. Here, we present a strategy to assess and prepare realistic trabecular structures for 3D printing using image analysis with the aim of preserving the structural elements. We discuss critical conditions of the printing system and present a 3-stage approach to adapt a trabecular structure from $\mu$CT data while incorporating knowledge about the printing system. In the first stage, an image-based extraction of solid and void structures is performed, which results in voxel- and graph-based representations of the extracted structures. These representations not only allow us to quantify geometrical properties such as pore size or strut geometry and length. But, since the graph represents the geometry and the topology of the initial structure, it can be used in the second stage to modify and adjust feature size, volume and sample size in an easy and consistent way. In the final reconstruction stage, the graph is then converted into a voxel representation preserving the topology of the initial structure. This stage generates a model with respect to the printing conditions to ensure a stable and controlled voxel placement during the printing process. Y1 - 2017 U6 - https://doi.org/10.1088/2057-1976/aa7611 VL - 3 IS - 3 PB - IOP Publishing ER - TY - GEN A1 - Homberg, Ulrike A1 - Baum, Daniel A1 - Prohaska, Steffen A1 - Günster, Jens A1 - Krauß-Schüler, Stefanie T1 - Adapting trabecular structures for 3D printing: an image processing approach based on µCT data N2 - Materials with a trabecular structure notably combine advantages such as lightweight, reasonable strength, and permeability for fluids. This combination of advantages is especially interesting for tissue engineering in trauma surgery and orthopedics. Bone-substituting scaffolds for instance are designed with a trabecular structure in order to allow cell migration for bone ingrowth and vascularization. An emerging and recently very popular technology to produce such complex, porous structures is 3D printing. However, several technological aspects regarding the scaffold architecture, the printable resolution, and the feature size have to be considered when fabricating scaffolds for bone tissue replacement and regeneration. Here, we present a strategy to assess and prepare realistic trabecular structures for 3D printing using image analysis with the aim of preserving the structural elements. We discuss critical conditions of the printing system and present a 3-stage approach to adapt a trabecular structure from $\mu$CT data while incorporating knowledge about the printing system. In the first stage, an image-based extraction of solid and void structures is performed, which results in voxel- and graph-based representations of the extracted structures. These representations not only allow us to quantify geometrical properties such as pore size or strut geometry and length. But, since the graph represents the geometry and the topology of the initial structure, it can be used in the second stage to modify and adjust feature size, volume and sample size in an easy and consistent way. In the final reconstruction stage, the graph is then converted into a voxel representation preserving the topology of the initial structure. This stage generates a model with respect to the printing conditions to ensure a stable and controlled voxel placement during the printing process. T3 - ZIB-Report - 17-26 KW - trabecular structures KW - image-based analysis KW - additive manufacturing KW - printability Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-64004 SN - 1438-0064 ER - TY - JOUR A1 - Redemann, Stefanie A1 - Baumgart, Johannes A1 - Lindow, Norbert A1 - Shelley, Michael A1 - Nazockdast, Ehssan A1 - Kratz, Andrea A1 - Prohaska, Steffen A1 - Brugués, Jan A1 - Fürthauer, Sebastian A1 - Müller-Reichert, Thomas T1 - C. elegans chromosomes connect to centrosomes by anchoring into the spindle network JF - Nature Communications N2 - The mitotic spindle ensures the faithful segregation of chromosomes. Here we combine the first large-scale serial electron tomography of whole mitotic spindles in early C. elegans embryos with live-cell imaging to reconstruct all microtubules in 3D and identify their plus- and minus-ends. We classify them as kinetochore (KMTs), spindle (SMTs) or astral microtubules (AMTs) according to their positions, and quantify distinct properties of each class. While our light microscopy and mutant studies show that microtubules are nucleated from the centrosomes, we find only a few KMTs directly connected to the centrosomes. Indeed, by quantitatively analysing several models of microtubule growth, we conclude that minus-ends of KMTs have selectively detached and depolymerized from the centrosome. In toto, our results show that the connection between centrosomes and chromosomes is mediated by an anchoring into the entire spindle network and that any direct connections through KMTs are few and likely very transient. Y1 - 2017 U6 - https://doi.org/10.1038/ncomms15288 VL - 8 IS - 15288 ER - TY - JOUR A1 - Paetsch, Olaf A1 - Baum, Daniel A1 - Prohaska, Steffen A1 - Ehrig, Karsten A1 - Ebell, Gino A1 - Meinel, Dietmar A1 - Heyn, Andreas T1 - Korrosionsverfolgung in 3D-computertomographischen Aufnahmen von Stahlbetonproben JF - DGZfP-Jahrestagung 2014 Konferenzband Y1 - 2014 ER - TY - GEN A1 - Paetsch, Olaf A1 - Baum, Daniel A1 - Ebell, Gino A1 - Ehrig, Karsten A1 - Heyn, Andreas A1 - Meinel, Dietmar A1 - Prohaska, Steffen T1 - Korrosionsverfolgung in 3D-computertomographischen Aufnahmen von Stahlbetonproben N2 - Kurzfassung. Durch die Alkalität des Betons wird Betonstahl dauerhaft vor Korrosion geschützt. Infolge von Chlorideintrag kann dieser Schutz nicht länger aufrechterhalten werden und führt zu Lochkorrosion. Die zerstörungsfreie Prüfung von Stahlbetonproben mit 3D-CT bietet die Möglichkeit, eine Probe mehrfach gezielt vorzuschädigen und den Korrosionsfortschritt zu untersuchen. Zur Quantifizierung des Schädigungsgrades müssen die bei dieser Untersuchung anfallenden großen Bilddaten mit Bildverarbeitungsmethoden ausgewertet werden. Ein wesentlicher Schritt dabei ist die Segmentierung der Bilddaten, bei der zwischen Korrosionsprodukt (Rost), Betonstahl (BSt), Beton, Rissen, Poren und Umgebung unterschieden werden muss. Diese Segmentierung bildet die Grundlage für statistische Untersuchungen des Schädigungsfortschritts. Hierbei sind die Änderung der BSt-Geometrie, die Zunahme von Korrosionsprodukten und deren Veränderung über die Zeit sowie ihrer räumlichen Verteilung in der Probe von Interesse. Aufgrund der Größe der CT-Bilddaten ist eine manuelle Segmentierung nicht durchführbar, so dass automatische Verfahren unabdingbar sind. Dabei ist insbesondere die Segmentierung der Korrosionsprodukte in den Bilddaten ein schwieriges Problem. Allein aufgrund der Grauwerte ist eine Zuordnung nahezu unmöglich, denn die Grauwerte von Beton und Korrosionsprodukt unterscheiden sich kaum. Eine formbasierte Suche ist nicht offensichtlich, da die Korrosionsprodukte in Beton diffuse Formen haben. Allerdings lässt sich Vorwissen über die Ausbreitung der Korrosionsprodukte nutzen. Sie bilden sich in räumlicher Nähe des BSt (in Bereichen vorheriger Volumenabnahme des BSt), entlang von Rissen sowie in Porenräumen, die direkt am BSt und in dessen Nahbereich liegen. Davon ausgehend wird vor der Korrosionsprodukterkennung zunächst eine BSt-Volumen-, Riss- und Porenerkennung durchgeführt. Dieser in der Arbeit näher beschriebene Schritt erlaubt es, halbautomatisch Startpunkte (Seed Points) für die Korrosionsprodukterkennung zu finden. Weiterhin werden verschiedene in der Bildverarbeitung bekannte Algorithmen auf ihre Eignung untersucht werden. T3 - ZIB-Report - 14-24 KW - Beton KW - Korrosionserkennung KW - Bildverarbeitung KW - Computertomografie KW - concrete KW - corrosiondetection KW - image processing KW - computed tomography Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-50912 SN - 1438-0064 ER - TY - GEN A1 - Osterland, Marc A1 - Benn, Andreas A1 - Prohaska, Steffen A1 - Schütte, Christof T1 - Single Cell Tracking in Phase-Contrast Microscopy T2 - EMBL Symposium 2015 - Seeing is Believing - Imaging the Processes of Life N2 - In this work, we developed an automatic algorithm to analyze cell migration in chemotaxis assays, based on phase-contrast time-lapse microscopy. While manual approaches are still widely used in recent publications, our algorithm is able to track hundreds of single cells per frame. The extracted paths are analysed with traditional geometrical approaches as well as diffusion-driven Markov state models (MSM). Based on these models, a detailed view on spatial and temporal effects is possible. Using our new approach on experimental data, we are able to distinguish between directed migration (e.g. towards a VEGF gradient) and random migration without favored direction. A calculation of the committor probabilities reveals that cells of the whole image area are more likely to migrate directly towards the VEGF than away from it during the first four hours. However, in absence of a chemoattractant, cells migrate more likely to their nearest image border. These conclusions are supported by the spatial mean directions. In a next step, the cell-cell interaction during migration and the migration of cell clusters will be analyzed. Furthermore, we want to observe phenotypical changes during migration based on fluorescence microscopy and machine learning. The algorithm is part of a collaborative platform which brings the experimental expertise of scientists from life sciences and the analytical knowledge of computer scientists together. This platform is built using web-based technologies with a responsive real-time user interface. All data, including raw and metadata as well as the accompanying results, will be stored in a secure and scalable compute cluster. The compute cluster provides sufficient space and computational power for modern image-based experiments and their analyses. Specific versions of data and results can be tagged to keep immutable records for archival. Y1 - 2015 ER - TY - CHAP A1 - Paetsch, Olaf A1 - Baum, Daniel A1 - Prohaska, Steffen A1 - Ehrig, Karsten A1 - Meinel, Dietmar A1 - Ebell, Gino T1 - 3D Corrosion Detection in Time-dependent CT Images of Concrete T2 - DIR-2015 Proceedings N2 - In civil engineering, the corrosion of steel reinforcements in structural elements of concrete bares a risk of stability-reduction, mainly caused by the exposure to chlorides. 3D computed tomography (CT) reveals the inner structure of concrete and allows one to investigate the corrosion with non-destructive testing methods. To carry out such investigations, specimens with a large artificial crack and an embedded steel rebar have been manufactured. 3D CT images of those specimens were acquired in the original state. Subsequently three cycles of electrochemical pre-damaging together with CT imaging were applied. These time series have been evaluated by means of image processing algorithms to segment and quantify the corrosion products. Visualization of the results supports the understanding of how corrosion propagates into cracks and pores. Furthermore, pitting of structural elements can be seen without dismantling. In this work, several image processing and visualization techniques are presented that have turned out to be particularly effective for the visualization and segmentation of corrosion products. Their combination to a workflow for corrosion analysis is the main contribution of this work. Y1 - 2015 UR - http://www.ndt.net/events/DIR2015/app/content/Paper/36_Paetsch.pdf ER - TY - GEN A1 - Knötel, David A1 - Seidel, Ronald A1 - Prohaska, Steffen A1 - Dean, Mason N. A1 - Baum, Daniel T1 - Automated Segmentation of Complex Patterns in Biological Tissues: Lessons from Stingray Tessellated Cartilage N2 - Introduction – Many biological structures show recurring tiling patterns on one structural level or the other. Current image acquisition techniques are able to resolve those tiling patterns to allow quantitative analyses. The resulting image data, however, may contain an enormous number of elements. This renders manual image analysis infeasible, in particular when statistical analysis is to be conducted, requiring a larger number of image data to be analyzed. As a consequence, the analysis process needs to be automated to a large degree. In this paper, we describe a multi-step image segmentation pipeline for the automated segmentation of the calcified cartilage into individual tesserae from computed tomography images of skeletal elements of stingrays. Methods – Besides applying state-of-the-art algorithms like anisotropic diffusion smoothing, local thresholding for foreground segmentation, distance map calculation, and hierarchical watershed, we exploit a graph-based representation for fast correction of the segmentation. In addition, we propose a new distance map that is computed only in the plane that locally best approximates the calcified cartilage. This distance map drastically improves the separation of individual tesserae. We apply our segmentation pipeline to hyomandibulae from three individuals of the round stingray (Urobatis halleri), varying both in age and size. Results – Each of the hyomandibula datasets contains approximately 3000 tesserae. To evaluate the quality of the automated segmentation, four expert users manually generated ground truth segmentations of small parts of one hyomandibula. These ground truth segmentations allowed us to compare the segmentation quality w.r.t. individual tesserae. Additionally, to investigate the segmentation quality of whole skeletal elements, landmarks were manually placed on all tesserae and their positions were then compared to the segmented tesserae. With the proposed segmentation pipeline, we sped up the processing of a single skeletal element from days or weeks to a few hours. T3 - ZIB-Report - 17-62 KW - micro-CT KW - image segmentation KW - 2D distance map KW - hierarchical watershed KW - stingray KW - tesserae KW - biological tilings KW - Amira Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-65785 SN - 1438-0064 ER - TY - JOUR A1 - Knötel, David A1 - Seidel, Ronald A1 - Prohaska, Steffen A1 - Dean, Mason N. A1 - Baum, Daniel T1 - Automated Segmentation of Complex Patterns in Biological Tissues: Lessons from Stingray Tessellated Cartilage JF - PLOS ONE N2 - Introduction – Many biological structures show recurring tiling patterns on one structural level or the other. Current image acquisition techniques are able to resolve those tiling patterns to allow quantitative analyses. The resulting image data, however, may contain an enormous number of elements. This renders manual image analysis infeasible, in particular when statistical analysis is to be conducted, requiring a larger number of image data to be analyzed. As a consequence, the analysis process needs to be automated to a large degree. In this paper, we describe a multi-step image segmentation pipeline for the automated segmentation of the calcified cartilage into individual tesserae from computed tomography images of skeletal elements of stingrays. Methods – Besides applying state-of-the-art algorithms like anisotropic diffusion smoothing, local thresholding for foreground segmentation, distance map calculation, and hierarchical watershed, we exploit a graph-based representation for fast correction of the segmentation. In addition, we propose a new distance map that is computed only in the plane that locally best approximates the calcified cartilage. This distance map drastically improves the separation of individual tesserae. We apply our segmentation pipeline to hyomandibulae from three individuals of the round stingray (Urobatis halleri), varying both in age and size. Results – Each of the hyomandibula datasets contains approximately 3000 tesserae. To evaluate the quality of the automated segmentation, four expert users manually generated ground truth segmentations of small parts of one hyomandibula. These ground truth segmentations allowed us to compare the segmentation quality w.r.t. individual tesserae. Additionally, to investigate the segmentation quality of whole skeletal elements, landmarks were manually placed on all tesserae and their positions were then compared to the segmented tesserae. With the proposed segmentation pipeline, we sped up the processing of a single skeletal element from days or weeks to a few hours. Y1 - 2017 U6 - https://doi.org/10.1371/journal.pone.0188018 ER - TY - GEN A1 - Kober, Cornelia A1 - Sader, Robert A1 - Zeilhofer, Hans-Florian A1 - Prohaska, Steffen A1 - Zachow, Stefan A1 - Deuflhard, Peter T1 - Anisotrope Materialmodellierung für den menschlichen Unterkiefer N2 - Im Rahmen der biomechanischen Simulation knöcherner Organe ist die Frage nach einer befriedigenden Materialbeschreibung nach wie vor ungelöst. Computertomographische Datensätze liefern eine räumliche Verteilung der (Röntgen-)Dichte und ermöglichen damit eine gute Darstellung der individuellen Geometrie. Weiter können die verschiedenen Materialbestandteile des Knochens, Spongiosa und Kortikalis, voneinander getrennt werden. Aber die richtungsabängige Information der Materialanisotropie ist verloren. In dieser Arbeit wird ein Ansatz für eine anisotrope Materialbeschreibung vorgestellt, die es ermöglicht, den Einfluss der individuellen knöchernen Struktur auf das makroskopische Materialverhalten abzuschätzen. T3 - ZIB-Report - 01-31 KW - menschlicher Unterkiefer KW - Simulation mit der Methode der finiten Elemente KW - innerer Aufbau des Knochens KW - anisotrope Elastizität Y1 - 2001 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-6574 ER - TY - JOUR A1 - Lindow, Norbert A1 - Brünig, Florian A1 - Dercksen, Vincent J. A1 - Fabig, Gunar A1 - Kiewisz, Robert A1 - Redemann, Stefanie A1 - Müller-Reichert, Thomas A1 - Prohaska, Steffen A1 - Baum, Daniel T1 - Semi-automatic stitching of filamentous structures in image stacks from serial-section electron tomography JF - Journal of Microscopy N2 - We present a software-assisted workflow for the alignment and matching of filamentous structures across a three-dimensional (3D) stack of serial images. This is achieved by combining automatic methods, visual validation, and interactive correction. After the computation of an initial automatic matching, the user can continuously improve the result by interactively correcting landmarks or matches of filaments. Supported by a visual quality assessment of regions that have been already inspected, this allows a trade-off between quality and manual labor. The software tool was developed in an interdisciplinary collaboration between computer scientists and cell biologists to investigate cell division by quantitative 3D analysis of microtubules (MTs) in both mitotic and meiotic spindles. For this, each spindle is cut into a series of semi-thick physical sections, of which electron tomograms are acquired. The serial tomograms are then stitched and non-rigidly aligned to allow tracing and connecting of MTs across tomogram boundaries. In practice, automatic stitching alone provides only an incomplete solution, because large physical distortions and a low signal-to-noise ratio often cause experimental difficulties. To derive 3D models of spindles despite dealing with imperfect data related to sample preparation and subsequent data collection, semi-automatic validation and correction is required to remove stitching mistakes. However, due to the large number of MTs in spindles (up to 30k) and their resulting dense spatial arrangement, a naive inspection of each MT is too time-consuming. Furthermore, an interactive visualization of the full image stack is hampered by the size of the data (up to 100 GB). Here, we present a specialized, interactive, semi-automatic solution that considers all requirements for large-scale stitching of filamentous structures in serial-section image stacks. To the best of our knowledge, it is the only currently available tool which is able to process data of the type and size presented here. The key to our solution is a careful design of the visualization and interaction tools for each processing step to guarantee real-time response, and an optimized workflow that efficiently guides the user through datasets. The final solution presented here is the result of an iterative process with tight feedback loops between the involved computer scientists and cell biologists. Y1 - 2021 U6 - https://doi.org/10.1111/jmi.13039 VL - 284 IS - 1 SP - 25 EP - 44 ER - TY - JOUR A1 - Lantzsch, Ina A1 - Yu, Che-Hang A1 - Chen, Yu-Zen A1 - Zimyanin, Vitaly A1 - Yazdkhasti, Hossein A1 - Lindow, Norbert A1 - Szentgyoergyi, Erik A1 - Pani, Ariel M A1 - Prohaska, Steffen A1 - Srayko, Martin A1 - Fürthauer, Sebastian A1 - Redemann, Stefanie T1 - Microtubule reorganization during female meiosis in C. elegans JF - eLife N2 - Most female meiotic spindles undergo striking morphological changes while transitioning from metaphase to anaphase. The ultra-structure of meiotic spindles, and how changes to this structure correlate with such dramatic spindle rearrangements remains largely unknown. To address this, we applied light microscopy, large-scale electron tomography and mathematical modeling of female meiotic \textit{Caenorhabditis elegans} spindles. Combining these approaches, we find that meiotic spindles are dynamic arrays of short microtubules that turn over within seconds. The results show that the metaphase to anaphase transition correlates with an increase in microtubule numbers and a decrease in their average length. Detailed analysis of the tomographic data revealed that the microtubule length changes significantly during the metaphase-to-anaphase transition. This effect is most pronounced for microtubules located within 150 nm of the chromosome surface. To understand the mechanisms that drive this transition, we developed a mathematical model for the microtubule length distribution that considers microtubule growth, catastrophe, and severing. Using Bayesian inference to compare model predictions and data, we find that microtubule turn-over is the major driver of the spindle reorganizations. Our data suggest that in metaphase only a minor fraction of microtubules, those closest to the chromosomes, are severed. The large majority of microtubules, which are not in close contact with chromosomes, do not undergo severing. Instead, their length distribution is fully explained by growth and catastrophe. This suggests that the most prominent drivers of spindle rearrangements are changes in nucleation and catastrophe rate. In addition, we provide evidence that microtubule severing is dependent on katanin. Y1 - 2021 U6 - https://doi.org/10.7554/eLife.58903 VL - 10 SP - e58903 ER - TY - JOUR A1 - Brence, Blaž A1 - Brummer, Josephine A1 - Dercksen, Vincent J. A1 - Özel, Mehmet Neset A1 - Kulkarni, Abhishkek A1 - Wolterhoff, Neele A1 - Prohaska, Steffen A1 - Hiesinger, Peter Robin A1 - Baum, Daniel T1 - Semi-automatic Geometrical Reconstruction and Analysis of Filopodia Dynamics in 4D Two-Photon Microscopy Images JF - bioRxiv N2 - Background: Filopodia are thin and dynamic membrane protrusions that play a crucial role in cell migration, axon guidance, and other processes where cells explore and interact with their surroundings. Historically, filopodial dynamics have been studied in great detail in 2D in cultured cells, and more recently in 3D culture as well as living brains. However, there is a lack of efficient tools to trace and track filopodia in 4D images of complex brain cells. Results: To address this issue, we have developed a semi-automatic workflow for tracing filopodia in 3D images and tracking the traced filopodia over time. The workflow was developed based on high-resolution data of photoreceptor axon terminals in the in vivo context of normal Drosophila brain development, but devised to be applicable to filopodia in any system, including at different temporal and spatial scales. In contrast to the pre-existing methods, our workflow relies solely on the original intensity images without the requirement for segmentation or complex preprocessing. The workflow was realized in C++ within the Amira software system and consists of two main parts, dataset pre-processing, and geometrical filopodia reconstruction, where each of the two parts comprises multiple steps. In this paper, we provide an extensive workflow description and demonstrate its versatility for two different axo-dendritic morphologies, R7 and Dm8 cells. Finally, we provide an analysis of the time requirements for user input and data processing. Conclusion: To facilitate simple application within Amira or other frameworks, we share the source code, which is available athttps://github.com/zibamira/filopodia-tool. Y1 - 2025 U6 - https://doi.org/10.1101/2025.05.20.654789 ER -