@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} }