TY - JOUR A1 - Knötel, David A1 - Seidel, Ronald A1 - Prohaska, Steffen A1 - Dean, Mason N. A1 - Baum, Daniel T1 - Automated Segmentation of Complex Patterns in Biological Tissues: Lessons from Stingray Tessellated Cartilage JF - PLOS ONE N2 - Introduction – Many biological structures show recurring tiling patterns on one structural level or the other. Current image acquisition techniques are able to resolve those tiling patterns to allow quantitative analyses. The resulting image data, however, may contain an enormous number of elements. This renders manual image analysis infeasible, in particular when statistical analysis is to be conducted, requiring a larger number of image data to be analyzed. As a consequence, the analysis process needs to be automated to a large degree. In this paper, we describe a multi-step image segmentation pipeline for the automated segmentation of the calcified cartilage into individual tesserae from computed tomography images of skeletal elements of stingrays. Methods – Besides applying state-of-the-art algorithms like anisotropic diffusion smoothing, local thresholding for foreground segmentation, distance map calculation, and hierarchical watershed, we exploit a graph-based representation for fast correction of the segmentation. In addition, we propose a new distance map that is computed only in the plane that locally best approximates the calcified cartilage. This distance map drastically improves the separation of individual tesserae. We apply our segmentation pipeline to hyomandibulae from three individuals of the round stingray (Urobatis halleri), varying both in age and size. Results – Each of the hyomandibula datasets contains approximately 3000 tesserae. To evaluate the quality of the automated segmentation, four expert users manually generated ground truth segmentations of small parts of one hyomandibula. These ground truth segmentations allowed us to compare the segmentation quality w.r.t. individual tesserae. Additionally, to investigate the segmentation quality of whole skeletal elements, landmarks were manually placed on all tesserae and their positions were then compared to the segmented tesserae. With the proposed segmentation pipeline, we sped up the processing of a single skeletal element from days or weeks to a few hours. Y1 - 2017 U6 - https://doi.org/10.1371/journal.pone.0188018 ER - TY - GEN A1 - Knötel, David A1 - Seidel, Ronald A1 - Zaslansky, Paul A1 - Prohaska, Steffen A1 - Dean, Mason N. A1 - Baum, Daniel T1 - Automated Segmentation of Complex Patterns in Biological Tissues: Lessons from Stingray Tessellated Cartilage (Supplementary Material) N2 - 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. Y1 - 2017 U6 - https://doi.org/10.12752/4.DKN.1.0 N1 - Supplementary data to reproduce and understand key results from the related publication, including original image data and processed data. ER - TY - JOUR A1 - Hoerth, Rebecca M. A1 - Baum, Daniel A1 - Knötel, David A1 - Prohaska, Steffen A1 - Willie, Bettina M. A1 - Duda, Georg A1 - Hege, Hans-Christian A1 - Fratzl, Peter A1 - Wagermaier, Wolfgang T1 - Registering 2D and 3D Imaging Data of Bone during Healing JF - Connective Tissue Research Y1 - 2015 U6 - https://doi.org/10.3109/03008207.2015.1005210 VL - 56 IS - 2 SP - 133 EP - 143 PB - Taylor & Francis ER -