@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{KnoetelSeidelWeaveretal., author = {Kn{\"o}tel, David and Seidel, Ronald and Weaver, James C. and Baum, Daniel and Dean, Mason N.}, title = {Segmentation of the Tessellated Mineralized Endoskeleton of Sharks and Rays}, series = {Poster, Tomography for Scientific Advancement symposium (ToScA), Manchester, UK, September 3 - 4, 2015}, journal = {Poster, Tomography for Scientific Advancement symposium (ToScA), Manchester, UK, September 3 - 4, 2015}, abstract = {The cartilaginous endoskeletons of sharks and rays are covered by tiles of mineralized cartilage called tesserae that enclose areas of unmineralized cartilage. These tesselated layers are vital to the growth as well as the material properties of the skeleton, providing both flexibility and strength. An understanding of the principles behind the tiling of the mineralized layer requires a quantitative analysis of shark and ray skeletal tessellation. However, since a single skeletal element comprises several thousand tesserae, manual segmentation is infeasible. We developed an automated segmentation pipeline that, working from micro-CT data, allows quantification of all tesserae in a skeletal element in less than an hour. Our segmentation algorithm relies on aspects we have learned of general tesseral morphology. In micro-CT scans, tesserae usually appear as round or star-shaped plate-like tiles, wider than deep and connected by mineralized intertesseral joints. Based on these observations, we exploit the distance map of the mineralized layer to separate individual tiles using a hierarchical watershed algorithm. Utilizing a two-dimensional distance map that measures the distance in the plane of the mineralized layer only greatly improves the segmentation. We developed post-processing techniques to quickly correct segmentation errors in regions where tesseral shape differs from the assumed shape. Evaluation of our results is done qualitatively by visual comparison with raw datasets, and quantitatively by comparison to manual segmentations. Furthermore, we generate two-dimensional abstractions of the tiling network based on the neighborhood, allowing representation of complex, biological forms as simpler geometries. We apply our newly developed techniques to the analysis of the left and right hyomandibulae of four ages of stingray enabling the first quantitative analyses of the tesseral tiling structure, while clarifying how these patterns develop across ontogeny.}, language = {en} } @misc{KnoetelSeidelHosnyetal., author = {Kn{\"o}tel, David and Seidel, Ronald and Hosny, Ahmed and Zaslansky, Paul and Weaver, James C. and Baum, Daniel and Dean, Mason N.}, title = {Understanding the Tiling Rules of the Tessellated Mineralized Endoskeleton of Sharks and Rays}, series = {Poster, Euro Bio-inspired Materials 2016, Potsdam, Germany, February 22 - 25, 2016}, journal = {Poster, Euro Bio-inspired Materials 2016, Potsdam, Germany, February 22 - 25, 2016}, abstract = {The endoskeletons of sharks and rays are composed of an unmineralized cartilaginous core, covered in an outer layer of mineralized tiles called tesserae. The tessellated layer is vital to the growth as well as the material properties of the skeletal element, providing both flexibility and strength. However, characterizing the relationship between tesseral size and shape, and skeletal growth and mechanics is challenging because tesserae are small (a few hundred micrometers wide), anchored to the surrounding tissue in complex three-dimensional ways, and occur in huge numbers. Using a custom-made semi-automatic segmentation algorithm, we present the first quantitative and three-dimensional description of tesserae in micro-CT scans of whole skeletal elements. Our segmentation algorithm relies on aspects we have learned of general tesseral morphology. We exploit the distance map of the mineralized layer to separate individual tiles using a hierarchical watershed algorithm. Additionally, we have developed post-processing techniques to quickly correct segmentation errors. Our data reveals that the tessellation is not regular, with tesserae showing a great range of shapes, sizes and number of neighbors. This is partly region-dependent: for example, thick, columnar tesserae are arranged in series along convex edges with small radius of curvature (RoC), whereas more brick-or disc-shaped tesserae are found in planar areas. We apply our newly developed techniques on the left and right hyomandibula (skeletal elements supporting the jaws) from four different ages of a stingray species, to clarify how tiling patterns develop across ontogeny and differ within and between individuals. We evaluate the functional consequences of tesseral morphologies using finite element analysis and 3d-printing, for a better understanding of shark skeletal mechanics, but also to extract fundamental engineering design principles of tiling arrangements on load-bearing three-dimensional objects.}, language = {en} } @misc{SeidelKnoetelBaumetal., author = {Seidel, Ronald and Kn{\"o}tel, David and Baum, Daniel and Weaver, James C. and Dean, Mason N.}, title = {Material and structural characterization of mineralized elasmobranch cartilage - lessons in repeated tiling patterns in mechanically loaded 3D objects}, series = {Poster, Tomography for Scientific Advancement symposium (ToScA), London, UK, September 1 - 3, 2014}, journal = {Poster, Tomography for Scientific Advancement symposium (ToScA), London, UK, September 1 - 3, 2014}, abstract = {Biological tissues achieve a wide range of properties and function, however with limited components. The organization of these constituent parts is a decisive factor in the impressive properties of biological materials, with tissues often exhibiting complex arrangements of hard and soft materials. The "tessellated" cartilage of the endoskeleton of sharks and rays, for example, is a natural composite of mineralized polygonal tiles (tesserae), collagen fiber bundles, and unmineralized cartilage, resulting in a material that is both flexible and strong, with optimal stiffness. The properties of the materials and the tiling geometry are vital to the growth and mechanics of the system, but had not been investigated due to the technical challenges involved. We use high-resolution materials characterization techniques (qBEI, µCT) to show that tesserae exhibit great variability in mineral density, supporting theories of accretive growth mechanisms. We present a developmental series of tesserae and outline the development of unique structural features that appear to function in load bearing and energy dissipation, with some structural features far exceeding cortical bone's mineral content and tissue stiffness. To examine interactions among tesserae, we developed an advanced tiling-recognition-algorithm to semi-automatically detect and isolate individual tiles in microCT scans of tesseral mats. The method allows quantification of shape variation across a wide area, allowing localization of regions of high/low reinforcement or flexibility in the skeleton. The combination of our material characterization and visualization techniques allows the first quantitative 3d description of anatomy and material properties of tesserae and the organization of tesseral networks in elasmobranch mineralized cartilage, providing insight into form-function relationships of the repeating tiled pattern. We aim to combine detailed knowledge of intra-tesseral morphology and mineralization to model the relationships of tesseral shapes and skeletal surface curvature, to understand fundamental tiling laws important for complex, mechanically loaded 3d objects.}, language = {en} } @misc{DeanHosnySeideletal., author = {Dean, Mason N. and Hosny, Ahmed and Seidel, Ronald and Baum, Daniel}, title = {Biological strategies for fatique and wear avoidance: lessons from stingray skeletons and teeth}, series = {Poster, Tomography for Scientific Advancement symposium (ToScA)}, journal = {Poster, Tomography for Scientific Advancement symposium (ToScA)}, 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{SeidelBlumerZaslanskyetal., author = {Seidel, Ronald and Blumer, Michael and Zaslansky, Paul and Kn{\"o}tel, David and Huber, Daniel R. and Weaver, James C. and Fratzl, Peter and Omelon, Sidney and Bertinetti, Luca and Dean, Mason N.}, title = {Ultrastructural, material and crystallographic description of endophytic masses - a possible damage response in shark and ray tessellated calcified cartilage}, series = {Journal of Structural Biology}, journal = {Journal of Structural Biology}, doi = {10.1016/j.jsb.2017.03.004}, abstract = {The cartilaginous endoskeletons of Elasmobranchs (sharks and rays) are reinforced superficially by minute, mineralized tiles, called tesserae. Unlike the bony skeletons of other vertebrates, elasmobranch skeletons have limited healing capability and their tissues' mechanisms for avoiding damage or managing it when it does occur are largely unknown. Here we describe an aberrant type of mineralized elasmobranch skeletal tissue called endophytic masses (EPMs), which grow into the uncalcified cartilage of the skeleton, but exhibit a strikingly different morphology compared to tesserae and other elasmobranch calcified tissues. We use biological and materials characterization techniques, including computed tomography, electron and light microscopy, x-ray and Raman spectroscopy and histology to characterize the morphology, ultrastructure and chemical composition of tesserae-associated EPMs in different elasmobranch species. EPMs appear to develop between and in intimate association with tesserae, but lack the lines of periodic growth and varying mineral density characteristic of tesserae. EPMs are mineral-dominated (high mineral and low organic content), comprised of birefringent bundles of large monetite or brushite crystals aligned end to end in long strings. Both Unusual skeletal mineralization in elasmobranchs tesserae and EPMs appear to develop in a type-2 collagen-based matrix, but in contrast to tesserae, all chondrocytes embedded or in contact with EPMs are dead and mineralized. The differences outlined between EPMs and tesserae demonstrate them to be distinct tissues. We discuss several possible reasons for EPM development, including tissue reinforcement, repair, and disruptions of mineralization processes, within the context of elasmobranch skeletal biology as well as descriptions of damage responses of other vertebrate mineralized tissues.}, language = {en} }