@misc{KnoetelSeidelProhaskaetal., 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}, 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{HombergBaumProhaskaetal., 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}, 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}, series = {Nature Communications}, 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{HombergBaumProhaskaetal., 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}, series = {Biomedical Physics \& Engineering Express}, volume = {3}, journal = {Biomedical Physics \& Engineering Express}, number = {3}, publisher = {IOP Publishing}, doi = {10.1088/2057-1976/aa7611}, 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{ZhukovaHiepenKnausetal., 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}, 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{KnoetelSeidelProhaskaetal., 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}, series = {PLOS ONE}, journal = {PLOS ONE}, doi = {10.1371/journal.pone.0188018}, 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{KnoetelSeidelZaslanskyetal., author = {Kn{\"o}tel, David and Seidel, Ronald and Zaslansky, Paul and Prohaska, Steffen and Dean, Mason N. and Baum, Daniel}, title = {Automated Segmentation of Complex Patterns in Biological Tissues: Lessons from Stingray Tessellated Cartilage (Supplementary Material)}, doi = {10.12752/4.DKN.1.0}, abstract = {Supplementary data to reproduce and understand key results from the related publication, including original image data and processed data. In particular, sections from hyomandibulae harvested from specimens of round stingray Urobatis halleri, donated from another study (DOI: 10.1002/etc.2564). Specimens were from sub-adults/adults collected by beach seine from collection sites in San Diego and Seal Beach, California, USA. The hyomandibulae were mounted in clay, sealed in ethanol-humidified plastic tubes and scanned with a Skyscan 1172 desktop μCT scanner (Bruker μCT, Kontich, Belgium) in association with another study (DOI: 10.1111/joa.12508). Scans for all samples were performed with voxel sizes of 4.89 μm at 59 kV source voltage and 167 μA source current, over 360◦ sample 120 rotation. For our segmentations, the datasets were resampled to a voxel size of 9.78 μm to reduce the size of the images and speed up processing. In addition, the processed data that was generated with the visualization software Amira with techniques described in the related publication based on the mentioned specimens.}, language = {en} } @article{ZhukovaHiepenKnausetal., 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}, series = {Advanced Healthcare Materials}, journal = {Advanced Healthcare Materials}, doi = {10.1002/adhm.201601244}, 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} } @inproceedings{KaplanBuchmannProhaskaetal., author = {Kaplan, Bernhard and Buchmann, Jens and Prohaska, Steffen and Laufer, Jan}, title = {Monte-Carlo-based inversion scheme for 3D quantitative photoacoustic tomography}, series = {Proc. of SPIE, Photons Plus Ultrasound: Imaging and Sensing 2017}, volume = {10064}, booktitle = {Proc. of SPIE, Photons Plus Ultrasound: Imaging and Sensing 2017}, doi = {10.1117/12.2251945}, pages = {100645J -- 100645J-13}, 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., 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}, series = {Proc. of SPIE, Photons Plus Ultrasound: Imaging and Sensing}, volume = {10064}, booktitle = {Proc. of SPIE, Photons Plus Ultrasound: Imaging and Sensing}, doi = {10.1117/12.2252359}, pages = {1006416 -- 1006416-8}, 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{KaplanLauferProhaskaetal., 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}, 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} }