TY - JOUR A1 - Buchmann, Jens A1 - Kaplan, Bernhard A1 - Powell, Samuel A1 - Prohaska, Steffen A1 - Laufer, Jan T1 - Quantitative PA tomography of high resolution 3-D images: experimental validation in tissue phantoms JF - Photoacoustics N2 - Quantitative photoacoustic tomography aims recover the spatial distribution of absolute chromophore concentrations and their ratios from deep tissue, high-resolution images. In this study, a model-based inversion scheme based on a Monte-Carlo light transport model is experimentally validated on 3-D multispectral images of a tissue phantom acquired using an all-optical scanner with a planar detection geometry. A calibrated absorber allowed scaling of the measured data during the inversion, while an acoustic correction method was employed to compensate the effects of limited view detection. Chromophore- and fluence-dependent step sizes and Adam optimization were implemented to achieve rapid convergence. High resolution 3-D maps of absolute concentrations and their ratios were recovered with high accuracy. Potential applications of this method include quantitative functional and molecular photoacoustic tomography of deep tissue in preclinical and clinical studies. Y1 - 2020 U6 - https://doi.org/10.1016/j.pacs.2019.100157 VL - 17 SP - 100157 ER - TY - JOUR A1 - Mohr, Gunther A1 - Altenburg, Simon J. A1 - Ulbricht, Alexander A1 - Heinrich, Philipp A1 - Baum, Daniel A1 - Maierhofer, Christiane A1 - Hilgenberg, Kai T1 - In-situ defect detection in laser powder bed fusion by using thermography and optical tomography – comparison to computed tomography JF - Metals Y1 - 2020 U6 - https://doi.org/10.3390/met10010103 VL - 10 IS - 1 SP - 103 ER - TY - CHAP A1 - von Tycowicz, Christoph T1 - Towards Shape-based Knee Osteoarthritis Classification using Graph Convolutional Networks T2 - 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020) N2 - We present a transductive learning approach for morphometric osteophyte grading based on geometric deep learning. We formulate the grading task as semi-supervised node classification problem on a graph embedded in shape space. To account for the high-dimensionality and non-Euclidean structure of shape space we employ a combination of an intrinsic dimension reduction together with a graph convolutional neural network. We demonstrate the performance of our derived classifier in comparisons to an alternative extrinsic approach. Y1 - 2020 U6 - https://doi.org/10.1109/ISBI45749.2020.9098687 ER - TY - JOUR A1 - Ziesche, Ralf F. A1 - Arlt, Tobias A1 - Finegan, Donal P. A1 - Heenan, Thomas M.M. A1 - Tengattini, Alessandro A1 - Baum, Daniel A1 - Kardjilov, Nikolay A1 - Markötter, Henning A1 - Manke, Ingo A1 - Kockelmann, Winfried A1 - Brett, Dan J.L. A1 - Shearing, Paul R. T1 - 4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique JF - Nature Communications N2 - The temporally and spatially resolved tracking of lithium intercalation and electrode degradation processes are crucial for detecting and understanding performance losses during the operation of lithium-batteries. Here, high-throughput X-ray computed tomography has enabled the identification of mechanical degradation processes in a commercial Li/MnO2 primary battery and the indirect tracking of lithium diffusion; furthermore, complementary neutron computed tomography has identified the direct lithium diffusion process and the electrode wetting by the electrolyte. Virtual electrode unrolling techniques provide a deeper view inside the electrode layers and are used to detect minor fluctuations which are difficult to observe using conventional three dimensional rendering tools. Moreover, the ‘unrolling’ provides a platform for correlating multi-modal image data which is expected to find wider application in battery science and engineering to study diverse effects e.g. electrode degradation or lithium diffusion blocking during battery cycling. Y1 - 2020 U6 - https://doi.org/10.1038/s41467-019-13943-3 VL - 11 SP - 777 ER - TY - JOUR A1 - Nava-Yazdani, Esfandiar A1 - Hege, Hans-Christian A1 - Sullivan, T. J. A1 - von Tycowicz, Christoph T1 - Geodesic Analysis in Kendall's Shape Space with Epidemiological Applications JF - Journal of Mathematical Imaging and Vision N2 - We analytically determine Jacobi fields and parallel transports and compute geodesic regression in Kendall’s shape space. Using the derived expressions, we can fully leverage the geometry via Riemannian optimization and thereby reduce the computational expense by several orders of magnitude over common, nonlinear constrained approaches. The methodology is demonstrated by performing a longitudinal statistical analysis of epidemiological shape data. As an example application we have chosen 3D shapes of knee bones, reconstructed from image data of the Osteoarthritis Initiative (OAI). Comparing subject groups with incident and developing osteoarthritis versus normal controls, we find clear differences in the temporal development of femur shapes. This paves the way for early prediction of incident knee osteoarthritis, using geometry data alone. Y1 - 2020 U6 - https://doi.org/10.1007/s10851-020-00945-w VL - 62 IS - 4 SP - 549 EP - 559 ER - TY - JOUR A1 - Banyassady, Bahareh A1 - Barba, Luis A1 - Mulzer, Wolfgang T1 - Time-Space Trade-Offs for Computing Euclidean Minimum Spanning Trees JF - Journal of Computational Geometry (JoCG) N2 - We present time-space trade-offs for computing the Euclidean minimum spanning tree of a set S of n point-sites in the plane. More precisely, we assume that S resides in a random-access memory that can only be read. The edges of the Euclidean minimum spanning tree EMST(S) have to be reported sequentially, and they cannot be accessed or modified afterwards. There is a parameter s in {1, ..., n} so that the algorithm may use O(s) cells of read-write memory (called the workspace) for its computations. Our goal is to find an algorithm that has the best possible running time for any given s between 1 and n. We show how to compute EMST(S) in O(((n^3)/(s^2)) log s) time with O(s) cells of workspace, giving a smooth trade-off between the two best-known bounds O(n^3) for s = 1 and O(n log n) for s = n. For this, we run Kruskal's algorithm on the "relative neighborhood graph" (RNG) of S. It is a classic fact that the minimum spanning tree of RNG(S) is exactly EMST(S). To implement Kruskal's algorithm with O(s) cells of workspace, we define s-nets, a compact representation of planar graphs. This allows us to efficiently maintain and update the components of the current minimum spanning forest as the edges are being inserted. Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?https://jocg.org/index.php/jocg/article/view/473 VL - 11(1) SP - 525 EP - 547 ER - TY - JOUR A1 - Chaumel, Júlia A1 - Schotte, Merlind A1 - Bizzarro, Joseph J. A1 - Zaslansky, Paul A1 - Fratzl, Peter A1 - Baum, Daniel A1 - Dean, Mason N. T1 - Co-aligned chondrocytes: Zonal morphological variation and structured arrangement of cell lacunae in tessellated cartilage JF - Bone N2 - In most vertebrates the embryonic cartilaginous skeleton is replaced by bone during development. During this process, cartilage cells (chondrocytes) mineralize the extracellular matrix and undergo apoptosis, giving way to bone cells (osteocytes). In contrast, sharks and rays (elasmobranchs) have cartilaginous skeletons throughout life, where only the surface mineralizes, forming a layer of tiles (tesserae). Elasmobranch chondrocytes, unlike those of other vertebrates, survive cartilage mineralization and are maintained alive in spaces (lacunae) within tesserae. However, the function(s) of the chondrocytes in the mineralized tissue remain unknown. Applying a custom analysis workflow to high-resolution synchrotron microCT scans of tesserae, we characterize the morphologies and arrangements of stingray chondrocyte lacunae, using lacunar morphology as a proxy for chondrocyte morphology. We show that the cell density is comparable in unmineralized and mineralized tissue from our study species and that cells maintain the similar volume even when they have been incorporated into tesserae. This discovery supports previous hypotheses that elasmobranch chondrocytes, unlike those of other taxa, do not proliferate, hypertrophy or undergo apoptosis during mineralization. Tessera lacunae show zonal variation in their shapes—being flatter further from and more spherical closer to the unmineralized cartilage matrix and larger in the center of tesserae— and show pronounced organization into parallel layers and strong orientation toward neighboring tesserae. Tesserae also exhibit local variation in lacunar density, with the density considerably higher near pores passing through the tesseral layer, suggesting pores and cells interact (e.g. that pores contain a nutrient source). We hypothesize that the different lacunar types reflect the stages of the tesserae formation process, while also representing local variation in tissue architecture and cell function. Lacunae are linked by small passages (canaliculi) in the matrix to form elongate series at the tesseral periphery and tight clusters in the center of tesserae, creating a rich connectivity among cells. The network arrangement and the shape variation of chondrocytes in tesserae indicate that cells may interact within and between tesserae and manage mineralization differently from chondrocytes in other vertebrates, perhaps performing analogous roles to osteocytes in bone. Y1 - 2020 U6 - https://doi.org/10.1016/j.bone.2020.115264 VL - 134 SP - 115264 ER - TY - GEN A1 - Chaumel, Júlia A1 - Schotte, Merlind A1 - Bizzarro, Joseph J. A1 - Zaslansky, Paul A1 - Fratzl, Peter A1 - Baum, Daniel A1 - Dean, Mason N. T1 - Co-aligned chondrocytes: Zonal morphological variation and structured arrangement of cell lacunae in tessellated cartilage N2 - In most vertebrates the embryonic cartilaginous skeleton is replaced by bone during development. During this process, cartilage cells (chondrocytes) mineralize the extracellular matrix and undergo apoptosis, giving way to bone cells (osteocytes). In contrast, sharks and rays (elasmobranchs) have cartilaginous skeletons throughout life, where only the surface mineralizes, forming a layer of tiles (tesserae). Elasmobranch chondrocytes, unlike those of other vertebrates, survive cartilage mineralization and are maintained alive in spaces (lacunae) within tesserae. However, the function(s) of the chondrocytes in the mineralized tissue remain unknown. Applying a custom analysis workflow to high-resolution synchrotron microCT scans of tesserae, we characterize the morphologies and arrangements of stingray chondrocyte lacunae, using lacunar morphology as a proxy for chondrocyte morphology. We show that the cell density is comparable in unmineralized and mineralized tissue from our study species and that cells maintain the similar volume even when they have been incorporated into tesserae. This discovery supports previous hypotheses that elasmobranch chondrocytes, unlike those of other taxa, do not proliferate, hypertrophy or undergo apoptosis during mineralization. Tessera lacunae show zonal variation in their shapes—being flatter further from and more spherical closer to the unmineralized cartilage matrix and larger in the center of tesserae— and show pronounced organization into parallel layers and strong orientation toward neighboring tesserae. Tesserae also exhibit local variation in lacunar density, with the density considerably higher near pores passing through the tesseral layer, suggesting pores and cells interact (e.g. that pores contain a nutrient source). We hypothesize that the different lacunar types reflect the stages of the tesserae formation process, while also representing local variation in tissue architecture and cell function. Lacunae are linked by small passages (canaliculi) in the matrix to form elongate series at the tesseral periphery and tight clusters in the center of tesserae, creating a rich connectivity among cells. The network arrangement and the shape variation of chondrocytes in tesserae indicate that cells may interact within and between tesserae and manage mineralization differently from chondrocytes in other vertebrates, perhaps performing analogous roles to osteocytes in bone. T3 - ZIB-Report - 20-04 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-77087 SN - 1438-0064 ER - TY - JOUR A1 - Schotte, Merlind A1 - Chaumel, Júlia A1 - Dean, Mason N. A1 - Baum, Daniel T1 - Image analysis pipeline for segmentation of a biological porosity network, the lacuno-canalicular system in stingray tesserae JF - MethodsX N2 - A prerequisite for many analysis tasks in modern comparative biology is the segmentation of 3-dimensional (3D) images of the specimens being investigated (e.g. from microCT data). Depending on the specific imaging technique that was used to acquire the images and on the image resolution, different segmentation tools will be required. While some standard tools exist that can often be applied for specific subtasks, building whole processing pipelines solely from standard tools is often difficult. Some tasks may even necessitate the implementation of manual interaction tools to achieve a quality that is sufficient for the subsequent analysis. In this work, we present a pipeline of segmentation tools that can be used for the semi-automatic segmentation and quantitative analysis of voids in tissue (i.e. internal structural porosity). We use this pipeline to analyze lacuno-canalicular networks in stingray tesserae from 3D images acquired with synchrotron microCT. * The first step of this processing pipeline, the segmentation of the tesserae, was performed using standard marker-based watershed segmentation. The efficient processing of the next two steps, that is, the segmentation of all lacunae spaces belonging to a specific tessera and the separation of these spaces into individual lacunae required modern, recently developed tools. * For proofreading, we developed a graph-based interactive method that allowed us to quickly split lacunae that were accidentally merged, and to merge lacunae that were wrongly split. * Finally, the tesserae and their corresponding lacunae were subdivided into anatomical regions of interest (structural wedges) using a semi- manual approach. Y1 - 2020 U6 - https://doi.org/10.1016/j.mex.2020.100905 VL - 7 SP - 100905 ER - TY - GEN A1 - Schotte, Merlind A1 - Chaumel, Júlia A1 - Dean, Mason N. A1 - Baum, Daniel T1 - Image analysis pipeline for segmentation of a biological porosity network, the lacuno-canalicular system in stingray tesserae N2 - A prerequisite for many analysis tasks in modern comparative biology is the segmentation of 3-dimensional (3D) images of the specimens being investigated (e.g. from microCT data). Depending on the specific imaging technique that was used to acquire the images and on the image resolution, different segmentation tools will be required. While some standard tools exist that can often be applied for specific subtasks, building whole processing pipelines solely from standard tools is often difficult. Some tasks may even necessitate the implementation of manual interaction tools to achieve a quality that is sufficient for the subsequent analysis. In this work, we present a pipeline of segmentation tools that can be used for the semi-automatic segmentation and quantitative analysis of voids in tissue (i.e. internal structural porosity). We use this pipeline to analyze lacuno-canalicular networks in stingray tesserae from 3D images acquired with synchrotron microCT. * The first step of this processing pipeline, the segmentation of the tesserae, was performed using standard marker-based watershed segmentation. The efficient processing of the next two steps, that is, the segmentation of all lacunae spaces belonging to a specific tessera and the separation of these spaces into individual lacunae required modern, recently developed tools. * For proofreading, we developed a graph-based interactive method that allowed us to quickly split lacunae that were accidentally merged, and to merge lacunae that were wrongly split. * Finally, the tesserae and their corresponding lacunae were subdivided into anatomical regions of interest (structural wedges) using a semi- manual approach. T3 - ZIB-Report - 20-12 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-78237 SN - 1438-0064 ER -