TY - JOUR A1 - Fogalli, Giovani Bressan A1 - Peres Line, Sérgio Roberto A1 - Baum, Daniel T1 - Segmentation of tooth enamel microstructure images using classical image processing and U-Net approaches JF - Frontiers in Imaging N2 - Tooth enamel is the hardest tissue in human organism, formed by prism layers in regularly alternating directions. These prisms form the Hunter-Schreger Bands (HSB) pattern when under side illumination, which is composed of light and dark stripes resembling fingerprints. We have shown in previous works that HSB pattern is highly variable, seems to be unique for each tooth and can be used as a biometric method for human identification. Since this pattern cannot be acquired with sensors, the HSB region in the digital photograph must be identified and correctly segmented from the rest of the tooth and background. Although these areas can be manually removed, this process is not reliable as excluded areas can vary according to the individual‘s subjective impression. Therefore, the aim of this work was to develop an algorithm that automatically selects the region of interest (ROI), thus, making the entire biometric process straightforward. We used two different approaches: a classical image processing method which we called anisotropy-based segmentation (ABS) and a machine learning method known as U-Net, a fully convolutional neural network. Both approaches were applied to a set of extracted tooth images. U-Net with some post processing outperformed ABS in the segmentation task with an Intersection Over Union (IOU) of 0.837 against 0.766. Even with a small dataset, U-Net proved to be a potential candidate for fully automated in-mouth application. However, the ABS technique has several parameters which allow a more flexible segmentation with interactive adjustments specific to image properties. Y1 - 2023 U6 - https://doi.org/10.3389/fimag.2023.1215764 VL - 2 ER - TY - JOUR A1 - Klenert, Nicolas A1 - Lepper, Verena A1 - Baum, Daniel T1 - A Local Iterative Approach for the Extraction of 2D Manifolds from Strongly Curved and Folded Thin-Layer Structures JF - IEEE Transactions on Visualization and Computer Graphics N2 - Ridge surfaces represent important features for the analysis of 3-dimensional (3D) datasets in diverse applications and are often derived from varying underlying data including flow fields, geological fault data, and point data, but they can also be present in the original scalar images acquired using a plethora of imaging techniques. Our work is motivated by the analysis of image data acquired using micro-computed tomography (μCT) of ancient, rolled and folded thin-layer structures such as papyrus, parchment, and paper as well as silver and lead sheets. From these documents we know that they are 2-dimensional (2D) in nature. Hence, we are particularly interested in reconstructing 2D manifolds that approximate the document’s structure. The image data from which we want to reconstruct the 2D manifolds are often very noisy and represent folded, densely-layered structures with many artifacts, such as ruptures or layer splitting and merging. Previous ridge-surface extraction methods fail to extract the desired 2D manifold for such challenging data. We have therefore developed a novel method to extract 2D manifolds. The proposed method uses a local fast marching scheme in combination with a separation of the region covered by fast marching into two sub-regions. The 2D manifold of interest is then extracted as the surface separating the two sub-regions. The local scheme can be applied for both automatic propagation as well as interactive analysis. We demonstrate the applicability and robustness of our method on both artificial data as well as real-world data including folded silver and papyrus sheets. Y1 - 2024 U6 - https://doi.org/10.1109/TVCG.2023.3327403 VL - 30 IS - 1 SP - 1260 EP - 1270 ER - TY - JOUR A1 - Zemann, Berit A1 - Le, Mai-Lee Van A1 - Sherlock, Rob E. A1 - Baum, Daniel A1 - Katija, Kakani A1 - Stach, Thomas T1 - Evolutionary traces of miniaturization in a giant – Comparative anatomy of brain and brain nerves in Bathochordaeus stygius (Tunicata, Appendicularia) JF - Journal of Morphology Y1 - 2023 U6 - https://doi.org/10.1002/jmor.21598 VL - 284 IS - 7 ER - TY - CHAP A1 - Brence, Blaž A1 - Fuchs, Joachim A1 - Hiesinger, Peter Robin A1 - Baum, Daniel ED - Garrison, Laura ED - Krueger, Robert T1 - Fully automated quantification of synaptic locations in multi-channel Drosophila photoreceptor microscopy data T2 - Eurographics Workshop on Visual Computing for Biology and Medicine N2 - The workload posed by image analysis remains a major bottleneck for advances across the life sciences. To address this challenge, we have developed a fully automated workflow for processing complex 3D multi-channel microscopy images. Specifically, our workflow addresses the analysis of photoreceptor synapses in confocal images of the Drosophila melanogaster optic lobe. The workflow consists of multiple stages, combining traditional and machine learning–based approaches for image analysis and visual computing. It performs segmentation of brain regions, photoreceptor instance identification, and precise localization of synapses. The key novelty of the workflow is an automatic alignment of synapses into a cylindrical reference coordinate system, enabling comparative synaptic analysis across photoreceptors. To demonstrate the workflow’s applicability, preliminary biological results and their interpretation based on 50 images are presented. While the workflow is still being improved further, here, we showcase its capacity for efficient and objective data processing for high-throughput neurobiological analyses. Y1 - 2025 U6 - https://doi.org/10.2312/vcbm.20251254 ER - TY - JOUR A1 - Vohra, Sumit Kumar A1 - Eberle, Maren A1 - Boulanger-Weill, Jonathan A1 - Petkova, Mariela D. A1 - Schuhknecht, Gregor F. P. A1 - Herrera, Kristian J. A1 - Kämpf, Florian A1 - Ruetten, Virginia M. S. A1 - Lichtman, Jeff W. A1 - Engert, Florian A1 - Randlett, Owen A1 - Bahl, Armin A1 - Isoe, Yasuko A1 - Hege, Hans-Christian A1 - Baum, Daniel T1 - Fishexplorer: A multimodal cellular atlas platform for neuronal circuit dissection in larval zebrafish JF - bioRxiv N2 - Understanding how neural circuits give rise to behavior requires comprehensive knowledge of neuronal morphology, connectivity, and function. Atlas platforms play a critical role in enabling the visualization, exploration, and dissemination of such information. Here, we present FishExplorer, an interactive and expandable community platform designed to integrate and analyze multimodal brain data from larval zebrafish. FishExplorer supports datasets acquired through light microscopy (LM), electron microscopy (EM), and X-ray imaging, all co-registered within a unified spatial coordinate system which enables seamless comparison of neuronal morphologies and synaptic connections. To further assist circuit analysis, FishExplorer includes a suite of tools for querying and visualizing connectivity at the whole-brain scale. By integrating data from recent large-scale EM reconstructions (presented in companion studies), FishExplorer enables researchers to validate circuit models, explore wiring principles, and generate new hypotheses. As a continuously evolving resource, FishExplorer is designed to facilitate collaborative discovery and serve the growing needs of the teleost neuroscience community. Y1 - 2025 U6 - https://doi.org/10.1101/2025.07.14.664689 ER - TY - JOUR A1 - Hu, Chenhao A1 - Tutika, Ravi A1 - Deng, Zhifei A1 - Jia, Zian A1 - Chen, Liuni A1 - Chen, Hongshun A1 - Geng, Yang A1 - Xiao, Xianghui A1 - Shevchenko, Pavel D. A1 - Pierre, Christoph A1 - Weaver, James C. A1 - Baum, Daniel A1 - Bartlett, Michael D. A1 - Li, Ling T1 - Mineralized sclerites in the gorgonian coral Leptogorgia chilensis as a natural jamming system JF - PNAS Y1 - 2025 U6 - https://doi.org/10.1073/pnas.2504541122 VL - 122 IS - 44 ER - TY - JOUR A1 - Sterzik, Anna A1 - Krone, Michael A1 - Baum, Daniel A1 - Cunningham, Douglas W. A1 - Lawonn, Kai T1 - Uncertainty Visualization for Biomolecular Structures: An Empirical Evaluation JF - IEEE Transactions on Visualization and Computer Graphics N2 - Uncertainty is an intrinsic property of almost all data, regardless of the data being measured, simulated, or generated. It can significantly influence the results and reliability of subsequent analysis steps. Clearly communicating uncertainties is crucial for informed decision-making and understanding, especially in biomolecular data, where uncertainty is often difficult to infer. Uncertainty visualization (UV) is a powerful tool for this purpose. However, previously proposed UV methods lack sufficient empirical evaluation. We collected and categorized visualization methods for portraying positional uncertainty in biomolecular structures. We then organized the methods into metaphorical groups and extracted nine representatives: color, clouds, ensemble, hulls, sausages, contours, texture, waves, and noise. We assessed their strengths and weaknesses in a twofold approach: expert assessments with six domain experts and three perceptual evaluations involving 1,756 participants. Through the expert assessments, we aimed to highlight the advantages and limitations of the individual methods for the application domain and discussed areas for necessary improvements. Through the perceptual evaluation, we investigated whether the visualizations are intuitively associated with uncertainty and whether the directionality of the mapping is perceived as intended. We also assessed the accuracy of inferring uncertainty values from the visualizations. Based on our results, we judged the appropriateness of the metaphors for encoding uncertainty and suggest further areas for improvement. Y1 - 2025 U6 - https://doi.org/10.1109/TVCG.2025.3596385 VL - 31 IS - 12 SP - 10296 EP - 10310 ER - TY - GEN A1 - Ehlers, Sarah A1 - Wessel, Andreas A1 - Baum, Daniel T1 - Segmentation of abdominal chordotonal organs based on semithin serial sections in the Rhododendron leafhopper Graphocephala fennahi (Cicadomorpha: Cicadellidae) N2 - For mating, leafhoppers (Cicadellidae) use substrate-borne vibrational signals to communicate. We provide the first complete description of the abdominal chordotonal organs that enable the perception of these signals. This supplementary data provides the aligned stack of 450 semithin serial sections of the first and second abdominal segment of an adult male Rhododendron leafhopper (Graphocephala fennahi). Further, this supplementary data comprises the segmentation files of five chordotonal organs, the exoskeleton, the segmental nerves and the spiracles of the first and the second abdominal segment. Due to time limitations, the structures of only one half of the body were segmented. The specimen was caught by hand net in September 2018 in Berlin-Tiergarten, Germany. Samples were embedded in Araldite® 502 resin and cut transversally in 1 μm thick sections using a Leica ultramicrotome and a DIATOME Histo Jumbo 6.0 mm diamond knife. Sections were placed on microscopic slides and stained with methylene blue/azur II. The images were taken by means of a 3DHISTECH PANNORAMIC SCAN II slide scanner in the Institute of Pathology Charité in Berlin-Mitte, Germany. Images with a voxel size of 0.273809 μm x 0.273809 μm x 1 μm where obtained. The images were converted from MRXS-files to TIFF-files with the 3DHistech software Slide Converter 2.3. Using Photoshop, the images were cropped to the same canvas size and artefacts were removed. All further steps, such as alignment and segmentation, were done with the software Amira. In order to facilitate the further processing of the dataset, the voxels where resampled to a size of 0.547619 μm x 0.547619 μm x 1 μm. Y1 - 2021 U6 - https://doi.org/10.12752/8326 N1 - Supplementary data to reproduce and understand the description of the morphology of the abdominal chordotonal organs in Graphocephala fennahi. ER - TY - JOUR A1 - Vohra, Sumit Kumar A1 - Harth, Philipp A1 - Isoe, Yasuko A1 - Bahl, Armin A1 - Fotowat, Haleh A1 - Engert, Florian A1 - Hege, Hans-Christian A1 - Baum, Daniel T1 - A Visual Interface for Exploring Hypotheses about Neural Circuits JF - IEEE Transactions on Visualization and Computer Graphics N2 - One of the fundamental problems in neurobiological research is to understand how neural circuits generate behaviors in response to sensory stimuli. Elucidating such neural circuits requires anatomical and functional information about the neurons that are active during the processing of the sensory information and generation of the respective response, as well as an identification of the connections between these neurons. With modern imaging techniques, both morphological properties of individual neurons as well as functional information related to sensory processing, information integration and behavior can be obtained. Given the resulting information, neurobiologists are faced with the task of identifying the anatomical structures down to individual neurons that are linked to the studied behavior and the processing of the respective sensory stimuli. Here, we present a novel interactive tool that assists neurobiologists in the aforementioned task by allowing them to extract hypothetical neural circuits constrained by anatomical and functional data. Our approach is based on two types of structural data: brain regions that are anatomically or functionally defined, and morphologies of individual neurons. Both types of structural data are interlinked and augmented with additional information. The presented tool allows the expert user to identify neurons using Boolean queries. The interactive formulation of these queries is supported by linked views, using, among other things, two novel 2D abstractions of neural circuits. The approach was validated in two case studies investigating the neural basis of vision-based behavioral responses in zebrafish larvae. Despite this particular application, we believe that the presented tool will be of general interest for exploring hypotheses about neural circuits in other species, genera and taxa. Y1 - 2024 U6 - https://doi.org/10.1109/TVCG.2023.3243668 VL - 30 IS - 7 SP - 3945 EP - 3958 ER - TY - GEN A1 - Vohra, Sumit Kumar A1 - Harth, Philipp A1 - Isoe, Yasuko A1 - Bahl, Armin A1 - Fotowat, Haleh A1 - Engert, Florian A1 - Hege, Hans-Christian A1 - Baum, Daniel T1 - A Visual Interface for Exploring Hypotheses about Neural Circuits N2 - One of the fundamental problems in neurobiological research is to understand how neural circuits generate behaviors in response to sensory stimuli. Elucidating such neural circuits requires anatomical and functional information about the neurons that are active during the processing of the sensory information and generation of the respective response, as well as an identification of the connections between these neurons. With modern imaging techniques, both morphological properties of individual neurons as well as functional information related to sensory processing, information integration and behavior can be obtained. Given the resulting information, neurobiologists are faced with the task of identifying the anatomical structures down to individual neurons that are linked to the studied behavior and the processing of the respective sensory stimuli. Here, we present a novel interactive tool that assists neurobiologists in the aforementioned task by allowing them to extract hypothetical neural circuits constrained by anatomical and functional data. Our approach is based on two types of structural data: brain regions that are anatomically or functionally defined, and morphologies of individual neurons. Both types of structural data are interlinked and augmented with additional information. The presented tool allows the expert user to identify neurons using Boolean queries. The interactive formulation of these queries is supported by linked views, using, among other things, two novel 2D abstractions of neural circuits. The approach was validated in two case studies investigating the neural basis of vision-based behavioral responses in zebrafish larvae. Despite this particular application, we believe that the presented tool will be of general interest for exploring hypotheses about neural circuits in other species, genera and taxa. T3 - ZIB-Report - 23-07 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-89932 SN - 1438-0064 ER - TY - JOUR A1 - Tomholt, Lara A1 - Baum, Daniel A1 - Wood, Robert J. A1 - Weaver, James C. T1 - High-throughput segmentation, data visualization, and analysis of sea star skeletal networks JF - Journal of Structural Biology N2 - The remarkably complex skeletal systems of the sea stars (Echinodermata, Asteroidea), consisting of hundreds to thousands of individual elements (ossicles), have intrigued investigators for more than 150 years. While the general features and structural diversity of isolated asteroid ossicles have been well documented in the literature, the task of mapping the spatial organization of these constituent skeletal elements in a whole-animal context represents an incredibly laborious process, and as such, has remained largely unexplored. To address this unmet need, particularly in the context of understanding structure-function relationships in these complex skeletal systems, we present an integrated approach that combines micro-computed tomography, semi-automated ossicle segmentation, data visualization tools, and the production of additively manufactured tangible models to reveal biologically relevant structural data that can be rapidly analyzed in an intuitive manner. In the present study, we demonstrate this high-throughput workflow by segmenting and analyzing entire skeletal systems of the giant knobby star, Pisaster giganteus, at four different stages of growth. The in-depth analysis, presented herein, provides a fundamental understanding of the three-dimensional skeletal architecture of the sea star body wall, the process of skeletal maturation during growth, and the relationship between skeletal organization and morphological characteristics of individual ossicles. The widespread implementation of this approach for investigating other species, subspecies, and growth series has the potential to fundamentally improve our understanding of asteroid skeletal architecture and biodiversity in relation to mobility, feeding habits, and environmental specialization in this fascinating group of echinoderms. Y1 - 2023 U6 - https://doi.org/10.1016/j.jsb.2023.107955 VL - 215 IS - 2 SP - 107955 ER - TY - JOUR A1 - Herter, Felix A1 - Hege, Hans-Christian A1 - Hadwiger, Markus A1 - Lepper, Verena A1 - Baum, Daniel T1 - Thin-Volume Visualization on Curved Domains JF - Computer Graphics Forum N2 - Thin, curved structures occur in many volumetric datasets. Their analysis using classical volume rendering is difficult because parts of such structures can bend away or hide behind occluding elements. This problem cannot be fully compensated by effective navigation alone, because structure-adapted navigation in the volume is cumbersome and only parts of the structure are visible in each view. We solve this problem by rendering a spatially transformed view into the volume so that an unobscured visualization of the entire curved structure is obtained. As a result, simple and intuitive navigation becomes possible. The domain of the spatial transform is defined by a triangle mesh that is topologically equivalent to an open disc and that approximates the structure of interest. The rendering is based on ray-casting in which the rays traverse the original curved sub-volume. In order to carve out volumes of varying thickness, the lengths of the rays as well as the position of the mesh vertices can be easily modified in a view-controlled manner by interactive painting. We describe a prototypical implementation and demonstrate the interactive visual inspection of complex structures from digital humanities, biology, medicine, and materials science. Displaying the structure as a whole enables simple inspection of interesting substructures in their original spatial context. Overall, we show that transformed views utilizing ray-casting-based volume rendering supported by guiding surface meshes and supplemented by local, interactive modifications of ray lengths and vertex positions, represent a simple but versatile approach to effectively visualize thin, curved structures in volumetric data. Y1 - 2021 U6 - https://doi.org/10.1111/cgf.14296 VL - 40 IS - 3 SP - 147 EP - 157 PB - Wiley-Blackwell Publishing Ltd. CY - United Kingdom ER - TY - JOUR A1 - Baum, Daniel A1 - Herter, Felix A1 - Larsen, John Møller A1 - Lichtenberger, Achim A1 - Raja, Rubina T1 - Revisiting the Jerash Silver Scroll: a new visual data analysis approach JF - Digital Applications in Archaeology and Cultural Heritage N2 - This article revisits a complexly folded silver scroll excavated in Jerash, Jordan in 2014 that was digitally examined in 2015. In this article we apply, examine and discuss a new virtual unfolding technique that results in a clearer image of the scroll’s 17 lines of writing. We also compare it to the earlier unfolding and discuss progress in general analytical tools. We publish the original and the new images as well as the unfolded volume data open access in order to make these available to researchers interested in optimising unfolding processes of various complexly folded materials. Y1 - 2021 U6 - https://doi.org/10.1016/j.daach.2021.e00186 VL - 21 SP - e00186 ER - TY - JOUR A1 - Becker, Kaitlyn P A1 - Teeple, Clark A1 - Charles, Nicholas A1 - Jung, Yeonsu A1 - Baum, Daniel A1 - Weaver, James C A1 - Mahadevan, L. A1 - Wood, Robert J T1 - Active entanglement enables stochastic, topological grasping JF - PNAS N2 - Grasping, in both biological and engineered mechanisms, can be highly sensitive to the gripper and object morphology, as well as perception and motion planning. Here we circumvent the need for feedback or precise planning by using an array of fluidically-actuated slender hollow elastomeric filaments to actively entangle with objects that vary in geometric and topological complexity. The resulting stochastic interactions enable a unique soft and conformable grasping strategy across a range of target objects that vary in size, weight, and shape. We experimentally evaluate the grasping performance of our strategy, and use a computational framework for the collective mechanics of flexible filaments in contact with complex objects to explain our findings. Overall, our study highlights how active collective entanglement of a filament array via an uncontrolled, spatially distributed scheme provides new options for soft, adaptable grasping. Y1 - 2022 U6 - https://doi.org/10.1073/pnas.2209819119 VL - 119 IS - 42 SP - e2209819119 ER - TY - JOUR A1 - Laguillo-Diego, Alejandra A1 - Kiewisz, Robert A1 - Martí-Gómez, Carlos A1 - Baum, Daniel A1 - Müller-Reichert, Thomas A1 - Vernos, Isabelle T1 - MCRS1 modulates the heterogeneity of microtubule minus-end morphologies in mitotic spindles JF - Molecular Biology of the Cell N2 - Faithful chromosome segregation requires the assembly of a bipolar spindle, consisting of two antiparallel microtubule (MT) arrays having most of their minus ends focused at the spindle poles and their plus ends overlapping in the spindle midzone. Spindle assembly, chromosome alignment and segregation require highly dynamic MTs. The plus ends of MTs have been extensively investigated; instead, their minus end structure remains poorly characterized. Here, we used large-scale electron tomography to study the morphology of the MT minus ends in 3D-reconstructed metaphase spindles in HeLa cells. In contrast to the homogeneous open morphology of the MT plus ends at the kinetochores, we found that MT minus ends are heterogeneous showing either open or closed morphologies. Silencing the minus-end specific stabilizer, MCRS1 increased the proportion of open MT minus ends. Altogether, these data suggest a correlation between the morphology and the dynamic state of the MT ends. Taking this heterogeneity of the MT minus end morphologies into account, our work indicates an unsynchronized behavior of MTs at the spindle poles, thus laying the ground for further studies on the complexity of MT dynamics regulation. Y1 - 2022 U6 - https://doi.org/10.1091/mbc.E22-08-0306-T VL - 34 IS - 1 ER - TY - CHAP A1 - Mayer, Julius A1 - Baum, Daniel A1 - Ambellan, Felix A1 - von Tycowicz, Christoph T1 - A Soft-Correspondence Approach to Shape-based Disease Grading with Graph Convolutional Networks T2 - Proceedings of Machine Learning Research N2 - Shape analysis provides principled means for understanding anatomical structures from medical images. The underlying notions of shape spaces, however, come with strict assumptions prohibiting the analysis of incomplete and/or topologically varying shapes. This work aims to alleviate these limitations by adapting the concept of soft correspondences. In particular, we present a graph-based learning approach for morphometric classification of disease states that is based on a generalized notion of shape correspondences in terms of functional maps. We demonstrate the performance of the derived classifier on the open-access ADNI database for differentiating normal controls and subjects with Alzheimer’s disease. Notably, our experiment shows that our approach can improve over state-of-the-art from geometric deep learning. Y1 - 2022 VL - 194 SP - 85 EP - 95 ER - TY - JOUR A1 - Mikula, Natalia A1 - Dörffel, Tom A1 - Baum, Daniel A1 - Hege, Hans-Christian T1 - An Interactive Approach for Identifying Structure Definitions JF - Computer Graphics Forum N2 - Our ability to grasp and understand complex phenomena is essentially based on recognizing structures and relating these to each other. For example, any meteorological description of a weather condition and explanation of its evolution recurs to meteorological structures, such as convection and circulation structures, cloud fields and rain fronts. All of these are spatiotemporal structures, defined by time-dependent patterns in the underlying fields. Typically, such a structure is defined by a verbal description that corresponds to the more or less uniform, often somewhat vague mental images of the experts. However, a precise, formal definition of the structures or, more generally, concepts is often desirable, e.g., to enable automated data analysis or the development of phenomenological models. Here, we present a systematic approach and an interactive tool to obtain formal definitions of spatiotemporal structures. The tool enables experts to evaluate and compare different structure definitions on the basis of data sets with time-dependent fields that contain the respective structure. Since structure definitions are typically parameterized, an essential part is to identify parameter ranges that lead to desired structures in all time steps. In addition, it is important to allow a quantitative assessment of the resulting structures simultaneously. We demonstrate the use of the tool by applying it to two meteorological examples: finding structure definitions for vortex cores and center lines of temporarily evolving tropical cyclones. Ideally, structure definitions should be objective and applicable to as many data sets as possible. However, finding such definitions, e.g., for the common atmospheric structures in meteorology, can only be a long-term goal. The proposed procedure, together with the presented tool, is just a first systematic approach aiming at facilitating this long and arduous way. Y1 - 2022 U6 - https://doi.org/10.1111/cgf.14543 VL - 41 IS - 3 SP - 321 EP - 332 ER - TY - JOUR A1 - Berio, Fidji A1 - Bayle, Yann A1 - Baum, Daniel A1 - Goudemand, Nicolas A1 - Debiais-Thibaud, Mélanie T1 - Hide and seek shark teeth in Random Forests: Machine learning applied to Scyliorhinus canicula populations JF - PeerJ - Aquatic Biology N2 - Shark populations that are distributed alongside a latitudinal gradient often display body size differences at sexual maturity and vicariance patterns related to their number of tooth files. Previous works have demonstrated that Scyliorhinus canicula exhibits distinct genetic structures, life history traits, and body size differences between populations inhabiting the North Atlantic Ocean and the Mediterranean Sea. In this work, we sample more than 3,000 S. canicula teeth from 56 specimens and provide and use a dataset containing their shape coordinates. We investigate tooth shape and form differences between a Mediterranean and an Atlantic S. canicula population using two approaches. Classification results show that the classical geometric morphometric framework is outperformed by an original Random Forests-based framework. Visually, both S. canicula populations share similar ontogenetic trends and timing of gynandric heterodonty emergence but the Atlantic population has bigger, blunter teeth, and less numerous accessory cusps than the Mediterranean population. According to the models, the populations are best differentiated based on their lateral tooth edges, which bear accessory cusps, and the tooth centroid sizes significantly improve classification performances. The differences observed are discussed in light of dietary and behavioural habits of the populations considered. The method proposed in this study could be further adapted to complement DNA analyses to identify shark species or populations based on tooth morphologies. This process would be of particular interest for fisheries management and identification of shark fossils. Y1 - 2022 U6 - https://doi.org/10.7717/peerj.13575 SP - 10:e13575 ER - TY - GEN A1 - Berio, Fidji A1 - Bayle, Yann A1 - Agret, Sylvie A1 - Baum, Daniel A1 - Goudemand, Nicolas A1 - Debiais-Thibaud, Mélanie T1 - 3D models related to the publication: Hide and seek shark teeth in Random Forests: Machine learning applied to Scyliorhinus canicula T2 - MorphoMuseuM N2 - The present dataset contains the 3D models analyzed in Berio, F., Bayle, Y., Baum, D., Goudemand, N., and Debiais-Thibaud, M. 2022. Hide and seek shark teeth in Random Forests: Machine learning applied to Scyliorhinus canicula. It contains the head surfaces of 56 North Atlantic and Mediterranean small-spotted catsharks Scyliorhinus canicula, from which tooth surfaces were further extracted to perform geometric morphometrics and machine learning. Y1 - 2022 U6 - https://doi.org/10.18563/journal.m3.164 ER - TY - JOUR A1 - Ehlers, Sarah A1 - Baum, Daniel A1 - Mühlethaler, Roland A1 - Hoch, Hannelore A1 - Bräunig, Peter T1 - Large abdominal mechanoreceptive sense organs in small plant-dwelling insects JF - Biology Letters N2 - The Hemiptera is the largest non-endopterygote insect order comprising approximately 98,000 recent species. All species of the suborders Cicadomorpha (leafhoppers, spittlebugs, treehoppers and cicadas) and Fulgoromorpha (planthoppers) feed by sucking sap from plant tissues and are thus often vectors for economically important phytopathogens. Except for the cicadas (Cicadomorpha: Cicadoidea: Cicadidae) which produce air-borne sounds, all species of the suborders Cicadomorpha and Fulgoromorpha communicate by vibrational (substrate-borne) signals. While the generation of these signals has been extensively investigated, the mechanisms of perception are poorly understood. This study provides a full description and 3D reconstruction of a large and complex array of six paired chordotonal organs in the first abdominal segments of the Rhododendron leafhopper Graphocephala fennahi (Cicadomorpha: Membracoidea: Cicadellidae). Further we were able to identify homologous organs in the closely related spittlebug Philaenus spumarius (Cicadomorpha: Cercopoidea: Aphrophoridae) and the planthopper Issus coleoptratus (Fulgoromorpha: Fulgoroidea: Issidae). The configuration is congruent with the abdominal chordotonal organs in cicadas, where one of them is an elaborate tympanal organ. This indicates that these organs, together with the tymbal organ constitute a synapomorphy of the Tymbalia (Hemiptera excl. Sternorrhyncha). Our results contribute to the understanding of the evolution from substrate-borne to airborne communication in insects. Y1 - 2022 U6 - https://doi.org/10.1098/rsbl.2022.0078 VL - 18 IS - 4 ER - TY - CHAP A1 - Paskin, Martha A1 - Dean, Mason A1 - Baum, Daniel A1 - von Tycowicz, Christoph T1 - A Kendall Shape Space Approach to 3D Shape Estimation from 2D Landmarks T2 - Computer Vision -- ECCV 2022 N2 - 3D shapes provide substantially more information than 2D images. However, the acquisition of 3D shapes is sometimes very difficult or even impossible in comparison with acquiring 2D images, making it necessary to derive the 3D shape from 2D images. Although this is, in general, a mathematically ill-posed problem, it might be solved by constraining the problem formulation using prior information. Here, we present a new approach based on Kendall’s shape space to reconstruct 3D shapes from single monocular 2D images. The work is motivated by an application to study the feeding behavior of the basking shark, an endangered species whose massive size and mobility render 3D shape data nearly impossible to obtain, hampering understanding of their feeding behaviors and ecology. 2D images of these animals in feeding position, however, are readily available. We compare our approach with state-of-the-art shape-based approaches both on human stick models and on shark head skeletons. Using a small set of training shapes, we show that the Kendall shape space approach is substantially more robust than previous methods and always results in plausible shapes. This is essential for the motivating application in which specimens are rare and therefore only few training shapes are available. Y1 - 2022 U6 - https://doi.org/10.1007/978-3-031-20086-1_21 SP - 363 EP - 379 PB - Springer Nature Switzerland ER - TY - GEN A1 - Paskin, Martha A1 - Baum, Daniel A1 - Dean, Mason N. A1 - von Tycowicz, Christoph T1 - A Kendall Shape Space Approach to 3D Shape Estimation from 2D Landmarks -- Source Code and Data N2 - Source code and novel dataset of basking shark head skeletons facilitating the reproduction of the results presented in 'A Kendall Shape Space Approach to 3D Shape Estimation from 2D Landmarks' - ECCV 2022. Y1 - 2022 U6 - https://doi.org/10.12752/8730 ER - TY - JOUR A1 - Hajarolasvadi, Noushin A1 - Sunkara, Vikram A1 - Khavnekar, Sagar A1 - Beck, Florian A1 - Brandt, Robert A1 - Baum, Daniel T1 - Volumetric macromolecule identification in cryo-electron tomograms using capsule networks JF - BMC Bioinformatics N2 - Background: Despite recent advances in cellular cryo-electron tomography (CET), developing automated tools for macromolecule identification in submolecular resolution remains challenging due to the lack of annotated data and high structural complexities. To date, the extent of the deep learning methods constructed for this problem is limited to conventional Convolutional Neural Networks (CNNs). Identifying macromolecules of different types and sizes is a tedious and time-consuming task. In this paper, we employ a capsule-based architecture to automate the task of macro- molecule identification, that we refer to as 3D-UCaps. In particular, the architecture is composed of three components: feature extractor, capsule encoder, and CNN decoder. The feature extractor converts voxel intensities of input sub-tomograms to activities of local features. The encoder is a 3D Capsule Network (CapsNet) that takes local features to generate a low-dimensional representation of the input. Then, a 3D CNN decoder reconstructs the sub-tomograms from the given representation by upsampling. Results: We performed binary and multi-class localization and identification tasks on synthetic and experimental data. We observed that the 3D-UNet and the 3D-UCaps had an F1−score mostly above 60% and 70%, respectively, on the test data. In both network architectures, we observed degradation of at least 40% in the F1-score when identifying very small particles (PDB entry 3GL1) compared to a large particle (PDB entry 4D8Q). In the multi-class identification task of experimental data, 3D-UCaps had an F1-score of 91% on the test data in contrast to 64% of the 3D-UNet. The better F1-score of 3D-UCaps compared to 3D-UNet is obtained by a higher precision score. We speculate this to be due to the capsule network employed in the encoder. To study the effect of the CapsNet-based encoder architecture further, we performed an ablation study and perceived that the F1-score is boosted as network depth is increased which is in contrast to the previously reported results for the 3D-UNet. To present a reproducible work, source code, trained models, data as well as visualization results are made publicly available. Conclusion: Quantitative and qualitative results show that 3D-UCaps successfully perform various downstream tasks including identification and localization of macro- molecules and can at least compete with CNN architectures for this task. Given that the capsule layers extract both the existence probability and the orientation of the molecules, this architecture has the potential to lead to representations of the data that are better interpretable than those of 3D-UNet. Y1 - 2022 U6 - https://doi.org/10.1186/s12859-022-04901-w VL - 23 IS - 360 ER - TY - JOUR A1 - Schmitt, Kira A1 - Titschack, Jürgen A1 - Baum, Daniel T1 - Polyp-Cavity Segmentation of Cold-Water Corals guided by Ambient Occlusion and Ambient Curvature JF - Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM) N2 - The segmentation of cavities in three-dimensional images of arbitrary objects is a difficult problem since the cavities are usually connected to the outside of the object without any difference in image intensity. Hence, the information whether a voxel belongs to a cavity or the outside needs to be derived from the ambient space. If a voxel is enclosed by object material, it is very likely that this voxel belongs to a cavity. However, there are dense structures where a voxel might still belong to the outside even though it is surrounded to a large degree by the object. This is, for example, the case for coral colonies. Therefore, additional information needs to be considered to distinguish between those cases. In this paper, we introduce the notion of ambient curvature, present an efficient way to compute it, and use it to segment coral polyp cavities by integrating it into the ambient occlusion framework. Moreover, we combine the ambient curvature with other ambient information in a Gaussian mixture model, trained from a few user scribbles, resulting in a significantly improved cavity segmentation. We showcase the superiority of our approach using four coral colonies of very different morphological types. While in this paper we restrict ourselves to coral data, we believe that the concept of ambient curvature is also useful for other data. Furthermore, our approach is not restricted to curvature but can be easily extended to exploit any properties given on an object's surface, thereby adjusting it to specific applications. Y1 - 2022 U6 - https://doi.org/10.2312/vcbm.20221189 ER - TY - JOUR A1 - Brence, Blaž A1 - Brummer, Josephine A1 - Dercksen, Vincent J. A1 - Özel, Mehmet Neset A1 - Kulkarni, Abhishkek A1 - Wolterhoff, Neele A1 - Prohaska, Steffen A1 - Hiesinger, Peter Robin A1 - Baum, Daniel T1 - Semi-automatic Geometrical Reconstruction and Analysis of Filopodia Dynamics in 4D Two-Photon Microscopy Images JF - bioRxiv N2 - Background: Filopodia are thin and dynamic membrane protrusions that play a crucial role in cell migration, axon guidance, and other processes where cells explore and interact with their surroundings. Historically, filopodial dynamics have been studied in great detail in 2D in cultured cells, and more recently in 3D culture as well as living brains. However, there is a lack of efficient tools to trace and track filopodia in 4D images of complex brain cells. Results: To address this issue, we have developed a semi-automatic workflow for tracing filopodia in 3D images and tracking the traced filopodia over time. The workflow was developed based on high-resolution data of photoreceptor axon terminals in the in vivo context of normal Drosophila brain development, but devised to be applicable to filopodia in any system, including at different temporal and spatial scales. In contrast to the pre-existing methods, our workflow relies solely on the original intensity images without the requirement for segmentation or complex preprocessing. The workflow was realized in C++ within the Amira software system and consists of two main parts, dataset pre-processing, and geometrical filopodia reconstruction, where each of the two parts comprises multiple steps. In this paper, we provide an extensive workflow description and demonstrate its versatility for two different axo-dendritic morphologies, R7 and Dm8 cells. Finally, we provide an analysis of the time requirements for user input and data processing. Conclusion: To facilitate simple application within Amira or other frameworks, we share the source code, which is available athttps://github.com/zibamira/filopodia-tool. Y1 - 2025 U6 - https://doi.org/10.1101/2025.05.20.654789 ER - TY - JOUR A1 - Brence, Blaž A1 - Wandelt, Laura R. A1 - Walter, Sophie A1 - Sigrist, Stephan J. A1 - Petzoldt, Astrid G. A1 - Baum, Daniel T1 - Semi-automatic 3D-quantification of in-vivo synapse formation JF - ResearchSquare N2 - Background: Synapses, as specialised cell-cell contacts, allow for a faithful and controlled signal transmission between a neuron and a target cell. Presynapses, the sites of neurotransmitter release, form de novo throughout the development of an organism. Although this process is fundamental to the development and function of synaptic circuits, how developing neurons control number and distribution of individual synapses remains poorly understood. In-vivo imaging analysis of synapse formation at the neuromuscular junction of anaesthetised Drosophila third instar larvae allows for spatial and temporal resolution of the underlying molecular processes. However, high-throughput, comprehensive analysis are hampered by the manual and time-consuming imaging analysis methods applied hitherto. Here, we focus on the early presynaptic formation steps, that is, the presynaptic seeding, initiated by the formation of transient Liprin-a/SYD1 seeding sites, either stabilised or disintegrated over a time span of 30-90 min. Results: To investigate the dynamics of the Liprin-a/SYD1 seeding sites, we developed an automated analysis pipeline for 3D confocal images from in-vivo imaging at distinct time points to analyse fluorescently labelled presynaptic protein dynamics during early synapse formation. The workflow is realised in the data analysis software Amira, utilising the hierarchical watershed algorithm, and was designed for automatic processing with an option for manual proofreading. Compared to the previous 2D manual quantification, this automated approach provides a higher sensitivity in single Liprin-a seeding site detection in low-intensity areas and in regions of dense seeding sites.In addition, it substantially reduces the work time. To account for possible errors occurring in the automated processing, we implemented an additional proofreading step allowing for a manual correction of Liprin-a seeding site segmentation and assignment, thus greatly improving the analysis while only marginally increasing work time by 10% to a total work time reduction of 80% compared to the 2D manual analysis paradigm. Conclusion: The process of synaptogenesis underlies the general principles of locomotion, learning and memory formation. The developed fast and accurate semi-automated 3D workflow provides a substantial progress in the analysis of this molecular process and its application can be easily extended to other dynamic in-vivo research approaches across species. Y1 - 2025 U6 - https://doi.org/10.21203/rs.3.rs-6073150/v1 ER - TY - JOUR A1 - Brence, Blaž A1 - Brummer, Josephine A1 - Dercksen, Vincent J. A1 - Özel, Mehmet Neset A1 - Kulkarni, Abhishek A1 - Wolterhoff, Neele A1 - Prohaska, Steffen A1 - Hiesinger, Peter Robin A1 - Baum, Daniel T1 - Semi-automatic geometrical reconstruction and analysis of filopodia dynamics in 4D two-photon microscopy images JF - BMC Bioinformatics N2 - Background: Filopodia are thin and dynamic membrane protrusions that play a crucial role in cell migration, axon guidance, and other processes where cells explore and interact with their surroundings. Historically, filopodial dynamics have been studied in great detail in 2D in cultured cells, and more recently in 3D culture as well as living brains. However, there is a lack of efficient tools to trace and track filopodia in 4D images of complex brain cells. Results: To address this issue, we have developed a semi-automatic workflow for tracing filopodia in 3D images and tracking the traced filopodia over time. The workflow was developed based on high-resolution data of photoreceptor axon terminals in the in vivo context of normal Drosophila brain development, but devised to be applicable to filopodia in any system, including at different temporal and spatial scales. In contrast to the pre-existing methods, our workflow relies solely on the original intensity images without the requirement for segmentation or complex preprocessing. The workflow was realized in C++ within the Amira software system and consists of two main parts, dataset pre-processing, and geometrical filopodia reconstruction, where each of the two parts comprises multiple steps. In this paper, we provide an extensive workflow description and demonstrate its versatility for two different axo-dendritic morphologies, R7 and Dm8 cells. Finally, we provide an analysis of the time requirements for user input and data processing. Conclusion: To facilitate simple application within Amira or other frameworks, we share the source code, which is available at https://github.com/zibamira/filopodia-tool. Y1 - 2026 U6 - https://doi.org/10.1186/s12859-026-06385-4 VL - 27 ER - TY - JOUR A1 - Eigen, Lennart A1 - Ladenburger, Pius A1 - Brence, Blaž A1 - Shubitidze, Ani A1 - Baum, Daniel A1 - Hildebrandt, Thomas A1 - Brecht, Michael T1 - Elephant trunk tip musculature reflects species differences in grasping behavior JF - Communications Biology N2 - Elephants use their trunks, muscular hydrostats, to perform a plethora of tasks. Trunk tip morphology as well as grasping behavior differ between elephant species. While African savanna elephants (Loxodonta africana) use their dorsal and ventral finger for pinching movements, Asian elephants (Elephas maximus) prefer to wrap around objects with their one dorsal finger and ventral bulb trunk tip lip. Moreover, E. maximus can flip their ventral bulb backwards to clamp objects behind the trunk tip. Whether trunk tip musculature differs between elephant species and muscle architecture is reflected by preferred grasping behavior is, however, not clear. In this study, we performed dense muscle fascicle reconstruction of three L. africana and three E. maximus hemi-trunk tips using a combination of manual and automated segmentation of high-resolution microfocus tomography (microCT) scans. We distinguish three types of muscle fascicles: longitudinal (bending and shortening), radial (elongating) and transversal muscle fascicles (elongating). We found that trunk tips of L. africana consist to one third of longitudinal and two thirds radial/transversal muscle fascicles, likely aiding in their grasping behavior, while E. maximus trunk tips consist to two thirds of longitudinal and one third radial/transversal muscle fascicles, which is advantageous for their wrapping and backward clamping behavior. Y1 - 2025 U6 - https://doi.org/10.1038/s42003-025-08998-6 VL - 8 ER - TY - JOUR A1 - Schmitt, Kira A1 - Titschack, Jürgen A1 - Baum, Daniel T1 - CoDA: Interactive Segmentation and Morphological Analysis of Dendroid Structures Exemplified on Stony Cold-Water Corals JF - IEEE Transactions on Visualization and Computer Graphics Y1 - 2026 U6 - https://doi.org/10.1109/TVCG.2026.3656066 ER - TY - JOUR A1 - Ngokingha Tchouto, Mireille A1 - Mehl, Julia A1 - Khomeijani Farahani, Saeed A1 - Baum, Daniel A1 - Duda, Georg T1 - Novel image registration approach for combining 2D Osterix and collagen bundles images with 3D µCT JF - Journal of Bone and Mineral Research Y1 - 2026 U6 - https://doi.org/10.1093/jbmrpl/ziag009 VL - 10 IS - 3 ER -