@inproceedings{FouardMalandainProhaskaetal.2004, author = {Fouard, C{\´e}line and Malandain, Gr{\´e}goire and Prohaska, Steffen and Westerhoff, Malte and Cassot, Francis and Mazel, Christophe and Asselot, Didier and Marc-Vergnes, Jean-Pierre}, title = {Skeletonization by blocks for large 3D datasets: Application to brain microcirculation}, booktitle = {IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'04)}, address = {Arlington, Virginia}, doi = {10.1109/ISBI.2004.1398481}, pages = {89 -- 92}, year = {2004}, language = {en} } @inproceedings{FouardMalandainProhaskaetal.2004, author = {Fouard, C{\´e}line and Malandain, Gr{\´e}goire and Prohaska, Steffen and Westerhoff, Malte and Cassot, Francis and Mazel, Christophe and Asselot, Didier and Marc-Vergnes, Jean-Pierre}, title = {Squelettisation par blocs pour des grands volumes de donn{\´e}es 3D}, booktitle = {Reconnaissance des Formes et Intelligence Artificielle (RFIA 2004)}, address = {Toulouse, France}, year = {2004}, language = {en} } @article{HutanuAllenBecketal.2006, author = {Hutanu, Andrei and Allen, Gabrielle and Beck, Stephen and Holub, Petr and Kaiser, Hartmut and Kulshrestha, Archit and Liska, Milos and MacLaren, Jon and Matyska, Ludek and Paruchuri, Ravi and Prohaska, Steffen and Seidel, Edward and Ullmer, Brygg and Venkataraman, Shalini}, title = {Distributed and collaborative visualization of large data sets using high-speed networks}, volume = {22(8)}, journal = {Future Generation Comp. Syst}, doi = {10.1016/j.future.2006.03.026}, pages = {1004 -- 1010}, year = {2006}, language = {en} } @article{HegeWeinkaufProhaskaetal.2005, author = {Hege, Hans-Christian and Weinkauf, Tino and Prohaska, Steffen and Hutanu, Andrei}, title = {Towards distributed visualization and analysis of large flow data}, volume = {48 (2)}, journal = {JSME International Journal, Series B}, pages = {241 -- 246}, year = {2005}, language = {en} } @inproceedings{DercksenProhaskaHege2005, author = {Dercksen, Vincent J. and Prohaska, Steffen and Hege, Hans-Christian}, title = {Fast cross-sectional display of large data sets}, booktitle = {IAPR Conference on Machine Vision Applications}, address = {Tsukuba, Japan}, pages = {336 -- 339}, year = {2005}, language = {en} } @inproceedings{Prohaska2006, author = {Prohaska, Steffen}, title = {Interaktive Visualisierung und Datenanalyse: Herausforderungen durch wachsende Datenmengen}, volume = {10}, booktitle = {Kartographische Schriften}, pages = {103 -- 110}, year = {2006}, language = {en} } @inproceedings{KaehlerProhaskaHutanuetal.2005, author = {K{\"a}hler, Ralf and Prohaska, Steffen and Hutanu, Andrei and Hege, Hans-Christian}, title = {Visualization of time-dependent remote adaptive mesh refinement data}, booktitle = {Proc. IEEE Visualization 2005}, address = {Minneapolis, USA}, doi = {10.1109/VISUAL.2005.1532793}, pages = {175 -- 182}, year = {2005}, language = {en} } @article{ThomsenLaibKolleretal.2005, author = {Thomsen, Jesper and Laib, Andreas and Koller, Bruno and Prohaska, Steffen and Mosekilde, L. and Gowin, Wolfgang}, title = {Stereological measures of trabecular bone structure: Comparison of 3D micro computed tomography with 2D histological sections in human proximal tibial bone biopsies}, volume = {218}, journal = {Journal of Microscopy}, pages = {171 -- 179}, year = {2005}, language = {en} } @inproceedings{ProhaskaHutanu2005, author = {Prohaska, Steffen and Hutanu, Andrei}, title = {Remote data access for interactive visualization}, booktitle = {13th Annual Mardi Gras Conference: Frontiers of Grid Applications and Technologies}, pages = {17 -- 22}, year = {2005}, language = {en} } @article{FouardMalandainProhaskaetal.2006, author = {Fouard, C{\´e}line and Malandain, Gr{\´e}goire and Prohaska, Steffen and Westerhoff, Malte}, title = {Blockwise processing applied to brain micro-vascular network study}, volume = {25}, journal = {IEEE Transactions on Medical Imaging}, number = {10}, doi = {10.1109/TMI.2006.880670}, pages = {1319 -- 1328}, year = {2006}, language = {en} } @article{ZaikinSaparinKurthsetal.2005, author = {Zaikin, Alexei and Saparin, Peter and Kurths, J{\"u}rgen and Prohaska, Steffen and Gowin, Wolfgang}, title = {Modeling resorption in 2D-CT and 3D μ-CT bone images}, volume = {15(9)}, journal = {Int. J. of Bif. and Chaos}, pages = {2995 -- 3009}, year = {2005}, language = {en} } @article{WeberTranfieldHoeoegetal.2014, author = {Weber, Britta and Tranfield, Erin M. and H{\"o}{\"o}g, Johanna L. and Baum, Daniel and Antony, Claude and Hyman, Tony and Verbavatz, Jean-Marc and Prohaska, Steffen}, title = {Automated stitching of microtubule centerlines across serial electron tomograms}, journal = {PLoS ONE}, doi = {10.1371/journal.pone.0113222}, pages = {e113222}, year = {2014}, language = {en} } @misc{RedemannWeberMoelleretal.2014, author = {Redemann, Stefanie and Weber, Britta and M{\"o}ller, Marit and Verbavatz, Jean-Marc and Hyman, Anthony and Baum, Daniel and Prohaska, Steffen and M{\"u}ller-Reichert, Thomas}, title = {The Segmentation of Microtubules in Electron Tomograms Using Amira}, journal = {Mitosis: Methods and Protocols}, publisher = {Springer}, doi = {10.1007/978-1-4939-0329-0_12}, pages = {261 -- 278}, year = {2014}, language = {en} } @misc{CostaOstrovskyMantonetal.2015, author = {Costa, Marta and Ostrovsky, Aaron D. and Manton, James D. and Prohaska, Steffen and Jefferis, Gregory S.X.E.}, title = {NBLAST: Rapid, sensitive comparison of neuronal structure and construction of neuron family databases}, journal = {bioRxiv preprint}, doi = {10.1101/006346}, year = {2015}, language = {en} } @misc{HoerthBaumKnoeteletal.2015, author = {Hoerth, Rebecca M. and Baum, Daniel and Kn{\"o}tel, David and Prohaska, Steffen and Willie, Bettina M. and Duda, Georg and Hege, Hans-Christian and Fratzl, Peter and Wagermaier, Wolfgang}, title = {Registering 2D and 3D Imaging Data of Bone during Healing}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-53426}, year = {2015}, abstract = {Purpose/Aims of the Study: Bone's hierarchical structure can be visualized using a variety of methods. Many techniques, such as light and electron microscopy generate two-dimensional (2D) images, while micro computed tomography (μCT) allows a direct representation of the three-dimensional (3D) structure. In addition, different methods provide complementary structural information, such as the arrangement of organic or inorganic compounds. The overall aim of the present study is to answer bone research questions by linking information of different 2D and 3D imaging techniques. A great challenge in combining different methods arises from the fact that they usually reflect different characteristics of the real structure. Materials and Methods: We investigated bone during healing by means of μCT and a couple of 2D methods. Backscattered electron images were used to qualitatively evaluate the tissue's calcium content and served as a position map for other experimental data. Nanoindentation and X-ray scattering experiments were performed to visualize mechanical and structural properties. Results: We present an approach for the registration of 2D data in a 3D μCT reference frame, where scanning electron microscopies serve as a methodic link. Backscattered electron images are perfectly suited for registration into μCT reference frames, since both show structures based on the same physical principles. We introduce specific registration tools that have been developed to perform the registration process in a semi-automatic way. Conclusions: By applying this routine, we were able to exactly locate structural information (e.g. mineral particle properties) in the 3D bone volume. In bone healing studies this will help to better understand basic formation, remodeling and mineralization processes.}, language = {en} } @article{HoerthBaumKnoeteletal.2015, author = {Hoerth, Rebecca M. and Baum, Daniel and Kn{\"o}tel, David and Prohaska, Steffen and Willie, Bettina M. and Duda, Georg and Hege, Hans-Christian and Fratzl, Peter and Wagermaier, Wolfgang}, title = {Registering 2D and 3D Imaging Data of Bone during Healing}, volume = {56}, journal = {Connective Tissue Research}, number = {2}, publisher = {Taylor \& Francis}, doi = {10.3109/03008207.2015.1005210}, pages = {133 -- 143}, year = {2015}, language = {en} } @misc{WeberTranfieldHoeoegetal.2014, author = {Weber, Britta and Tranfield, Erin M. and H{\"o}{\"o}g, Johanna L. and Baum, Daniel and Antony, Claude and Hyman, Tony and Verbavatz, Jean-Marc and Prohaska, Steffen}, title = {Automated stitching of microtubule centerlines across serial electron tomograms}, issn = {1438-0064}, doi = {10.1371/journal.pone.0113222}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-52958}, year = {2014}, abstract = {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.}, language = {en} } @misc{KaplanLauferProhaskaetal.2017, author = {Kaplan, Bernhard and Laufer, Jan and Prohaska, Steffen and Buchmann, Jens}, title = {Monte-Carlo-based inversion scheme for 3D quantitative photoacoustic tomography}, issn = {1438-0064}, doi = {10.1117/12.2251945}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-62318}, year = {2017}, abstract = {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.}, language = {en} } @inproceedings{KaplanBuchmannProhaskaetal.2017, author = {Kaplan, Bernhard and Buchmann, Jens and Prohaska, Steffen and Laufer, Jan}, title = {Monte-Carlo-based inversion scheme for 3D quantitative photoacoustic tomography}, volume = {10064}, booktitle = {Proc. of SPIE, Photons Plus Ultrasound: Imaging and Sensing 2017}, doi = {10.1117/12.2251945}, pages = {100645J -- 100645J-13}, year = {2017}, abstract = {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.}, language = {en} } @inproceedings{BuchmannKaplanProhaskaetal.2017, author = {Buchmann, Jens and Kaplan, Bernhard and Prohaska, Steffen and Laufer, Jan}, title = {Experimental validation of a Monte-Carlo-based inversion scheme for 3D quantitative photoacoustic tomography}, volume = {10064}, booktitle = {Proc. of SPIE, Photons Plus Ultrasound: Imaging and Sensing}, doi = {10.1117/12.2252359}, pages = {1006416 -- 1006416-8}, year = {2017}, abstract = {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.}, language = {en} } @misc{ZhukovaHiepenKnausetal.2017, author = {Zhukova, Yulia and Hiepen, Christian and Knaus, Petra and Osterland, Marc and Prohaska, Steffen and Dunlop, John W. C. and Fratzl, Peter and Skorb, Ekaterina V.}, title = {The role of titanium surface nanotopography on preosteoblast morphology, adhesion and migration}, issn = {1438-0064}, doi = {10.1002/adhm.201601244}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-63053}, year = {2017}, abstract = {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.}, language = {en} } @article{HombergBaumProhaskaetal.2017, author = {Homberg, Ulrike and Baum, Daniel and Prohaska, Steffen and G{\"u}nster, Jens and Krauß-Sch{\"u}ler, Stefanie}, title = {Adapting trabecular structures for 3D printing: an image processing approach based on µCT data}, volume = {3}, journal = {Biomedical Physics \& Engineering Express}, number = {3}, publisher = {IOP Publishing}, doi = {10.1088/2057-1976/aa7611}, year = {2017}, abstract = {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.}, language = {en} } @misc{HombergBaumProhaskaetal.2017, author = {Homberg, Ulrike and Baum, Daniel and Prohaska, Steffen and G{\"u}nster, Jens and Krauß-Sch{\"u}ler, Stefanie}, title = {Adapting trabecular structures for 3D printing: an image processing approach based on µCT data}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-64004}, year = {2017}, abstract = {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.}, language = {en} } @article{RedemannBaumgartLindowetal.2017, author = {Redemann, Stefanie and Baumgart, Johannes and Lindow, Norbert and Shelley, Michael and Nazockdast, Ehssan and Kratz, Andrea and Prohaska, Steffen and Brugu{\´e}s, Jan and F{\"u}rthauer, Sebastian and M{\"u}ller-Reichert, Thomas}, title = {C. elegans chromosomes connect to centrosomes by anchoring into the spindle network}, volume = {8}, journal = {Nature Communications}, number = {15288}, doi = {10.1038/ncomms15288}, year = {2017}, abstract = {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.}, language = {en} } @article{PaetschBaumProhaskaetal.2014, author = {Paetsch, Olaf and Baum, Daniel and Prohaska, Steffen and Ehrig, Karsten and Ebell, Gino and Meinel, Dietmar and Heyn, Andreas}, title = {Korrosionsverfolgung in 3D-computertomographischen Aufnahmen von Stahlbetonproben}, journal = {DGZfP-Jahrestagung 2014 Konferenzband}, year = {2014}, language = {de} } @misc{PaetschBaumEbelletal.2014, author = {Paetsch, Olaf and Baum, Daniel and Ebell, Gino and Ehrig, Karsten and Heyn, Andreas and Meinel, Dietmar and Prohaska, Steffen}, title = {Korrosionsverfolgung in 3D-computertomographischen Aufnahmen von Stahlbetonproben}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-50912}, year = {2014}, abstract = {Kurzfassung. Durch die Alkalit{\"a}t des Betons wird Betonstahl dauerhaft vor Korrosion gesch{\"u}tzt. Infolge von Chlorideintrag kann dieser Schutz nicht l{\"a}nger aufrechterhalten werden und f{\"u}hrt zu Lochkorrosion. Die zerst{\"o}rungsfreie Pr{\"u}fung von Stahlbetonproben mit 3D-CT bietet die M{\"o}glichkeit, eine Probe mehrfach gezielt vorzusch{\"a}digen und den Korrosionsfortschritt zu untersuchen. Zur Quantifizierung des Sch{\"a}digungsgrades m{\"u}ssen 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 f{\"u}r statistische Untersuchungen des Sch{\"a}digungsfortschritts. Hierbei sind die {\"A}nderung der BSt-Geometrie, die Zunahme von Korrosionsprodukten und deren Ver{\"a}nderung {\"u}ber die Zeit sowie ihrer r{\"a}umlichen Verteilung in der Probe von Interesse. Aufgrund der Gr{\"o}ße der CT-Bilddaten ist eine manuelle Segmentierung nicht durchf{\"u}hrbar, 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 unm{\"o}glich, 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 l{\"a}sst sich Vorwissen {\"u}ber die Ausbreitung der Korrosionsprodukte nutzen. Sie bilden sich in r{\"a}umlicher N{\"a}he des BSt (in Bereichen vorheriger Volumenabnahme des BSt), entlang von Rissen sowie in Porenr{\"a}umen, die direkt am BSt und in dessen Nahbereich liegen. Davon ausgehend wird vor der Korrosionsprodukterkennung zun{\"a}chst eine BSt-Volumen-, Riss- und Porenerkennung durchgef{\"u}hrt. Dieser in der Arbeit n{\"a}her beschriebene Schritt erlaubt es, halbautomatisch Startpunkte (Seed Points) f{\"u}r die Korrosionsprodukterkennung zu finden. Weiterhin werden verschiedene in der Bildverarbeitung bekannte Algorithmen auf ihre Eignung untersucht werden.}, language = {de} } @misc{OsterlandBennProhaskaetal.2015, author = {Osterland, Marc and Benn, Andreas and Prohaska, Steffen and Sch{\"u}tte, Christof}, title = {Single Cell Tracking in Phase-Contrast Microscopy}, journal = {EMBL Symposium 2015 - Seeing is Believing - Imaging the Processes of Life}, year = {2015}, abstract = {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.}, language = {en} } @inproceedings{PaetschBaumProhaskaetal.2015, author = {Paetsch, Olaf and Baum, Daniel and Prohaska, Steffen and Ehrig, Karsten and Meinel, Dietmar and Ebell, Gino}, title = {3D Corrosion Detection in Time-dependent CT Images of Concrete}, booktitle = {DIR-2015 Proceedings}, year = {2015}, abstract = {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.}, language = {en} } @misc{KnoetelSeidelProhaskaetal.2017, author = {Kn{\"o}tel, David and Seidel, Ronald and Prohaska, Steffen and Dean, Mason N. and Baum, Daniel}, title = {Automated Segmentation of Complex Patterns in Biological Tissues: Lessons from Stingray Tessellated Cartilage}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-65785}, year = {2017}, abstract = {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.}, language = {en} } @article{KnoetelSeidelProhaskaetal.2017, author = {Kn{\"o}tel, David and Seidel, Ronald and Prohaska, Steffen and Dean, Mason N. and Baum, Daniel}, title = {Automated Segmentation of Complex Patterns in Biological Tissues: Lessons from Stingray Tessellated Cartilage}, journal = {PLOS ONE}, doi = {10.1371/journal.pone.0188018}, year = {2017}, abstract = {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.}, language = {en} } @misc{KoberSaderZeilhoferetal.2001, author = {Kober, Cornelia and Sader, Robert and Zeilhofer, Hans-Florian and Prohaska, Steffen and Zachow, Stefan and Deuflhard, Peter}, title = {Anisotrope Materialmodellierung f{\"u}r den menschlichen Unterkiefer}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-6574}, number = {01-31}, year = {2001}, abstract = {Im Rahmen der biomechanischen Simulation kn{\"o}cherner Organe ist die Frage nach einer befriedigenden Materialbeschreibung nach wie vor ungel{\"o}st. Computertomographische Datens{\"a}tze liefern eine r{\"a}umliche Verteilung der (R{\"o}ntgen-)Dichte und erm{\"o}glichen damit eine gute Darstellung der individuellen Geometrie. Weiter k{\"o}nnen die verschiedenen Materialbestandteile des Knochens, Spongiosa und Kortikalis, voneinander getrennt werden. Aber die richtungsab{\"a}ngige Information der Materialanisotropie ist verloren. In dieser Arbeit wird ein Ansatz f{\"u}r eine anisotrope Materialbeschreibung vorgestellt, die es erm{\"o}glicht, den Einfluss der individuellen kn{\"o}chernen Struktur auf das makroskopische Materialverhalten abzusch{\"a}tzen.}, language = {de} } @article{LindowBruenigDercksenetal.2021, author = {Lindow, Norbert and Br{\"u}nig, Florian and Dercksen, Vincent J. and Fabig, Gunar and Kiewisz, Robert and Redemann, Stefanie and M{\"u}ller-Reichert, Thomas and Prohaska, Steffen and Baum, Daniel}, title = {Semi-automatic stitching of filamentous structures in image stacks from serial-section electron tomography}, volume = {284}, journal = {Journal of Microscopy}, number = {1}, doi = {10.1111/jmi.13039}, pages = {25 -- 44}, year = {2021}, abstract = {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.}, language = {en} } @article{LantzschYuChenetal.2021, author = {Lantzsch, Ina and Yu, Che-Hang and Chen, Yu-Zen and Zimyanin, Vitaly and Yazdkhasti, Hossein and Lindow, Norbert and Szentgyoergyi, Erik and Pani, Ariel M and Prohaska, Steffen and Srayko, Martin and F{\"u}rthauer, Sebastian and Redemann, Stefanie}, title = {Microtubule reorganization during female meiosis in C. elegans}, volume = {10}, journal = {eLife}, doi = {10.7554/eLife.58903}, pages = {e58903}, year = {2021}, abstract = {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.}, language = {en} } @article{BrenceBrummerDercksenetal.2025, author = {Brence, Blaž and Brummer, Josephine and Dercksen, Vincent J. and {\"O}zel, Mehmet Neset and Kulkarni, Abhishkek and Wolterhoff, Neele and Prohaska, Steffen and Hiesinger, Peter Robin and Baum, Daniel}, title = {Semi-automatic Geometrical Reconstruction and Analysis of Filopodia Dynamics in 4D Two-Photon Microscopy Images}, journal = {bioRxiv}, doi = {10.1101/2025.05.20.654789}, year = {2025}, abstract = {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.}, language = {en} }