VCBM 2025: Eurographics Workshop on Visual Computing for Biology and Medicine

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https://diglib.eg.org/handle/10.2312/3607232

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    Visual Analysis of Time-Dependent Observables in Cell Signaling Simulations
    (The Eurographics Association, 2025) Cibulski, Lena; Haack, Fiete; Uhrmacher, Adelinde; Bruckner, Stefan; Garrison, Laura; Krueger, Robert
    The ability of a cell to communicate with its environment is essential for key cellular functions like replication, metabolism, or cell fate decisions. The involved molecular mechanisms are highly dynamic and difficult to capture experimentally. Simulation studies offer a valuable means for exploring and predicting how cell signaling processes unfold. We present a design study on the visual analysis of such studies to support 1) modelers in calibrating model parameters such that the simulated signal responses over time reflect reference behavior from cell biology research and 2) cell biologists in exploring the influence of receptor trafficking on the efficiency of signal transmission within the cell. We embed time series plots into parallel coordinates to enable a simultaneous analysis of model parameters and temporal outputs. A usage scenario illustrates how our approach assists with typical tasks such as assessing the plausibility of temporal outputs or their sensitivity across model configurations.
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    Clusters in Focus: A Simple and Robust Detail-On-Demand Dashboard for Patient Data
    (The Eurographics Association, 2025) Schilcher, Lukas; Waldert, Peter; Kantz, Benedikt; Schreck, Tobias; Garrison, Laura; Krueger, Robert
    Exploring tabular datasets to understand how different feature pairs partition data into meaningful cohorts is crucial in domains such as biomarker discovery, yet comparing clusters across multiple feature pair projections is challenging. We introduce Clusters in Focus, an interactive visual analytics dashboard designed to address this gap. Clusters in Focus employs a threepanel coordinated view: a Data Panel offers multiple perspectives (tabular, heatmap, condensed with histograms / SHAP values) for initial data exploration; a Selection Panel displays the 2D clustering (K-Means/DBSCAN) for a user-selected feature pair; and a novel Cluster Similarity Panel featuring two switchable views for comparing clusters. A ranked list enables the identification of top-matching feature pairs, while an interactive similarity matrix with reordering capabilities allows for the discovery of global structural patterns and groups of related features. This dual-view design supports both focused querying and broad visual exploration. A use case on a Parkinson's disease speech dataset demonstrates the tool's effectiveness in revealing relationships between different feature pairs characterizing the same patient subgroup.
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    Fully Automated Quantification of Synaptic Localization in Multi-channel Drosophila Photoreceptor Microscopy Data
    (The Eurographics Association, 2025) Brence, Blaz; Fuchs, Joachim; Hiesinger, Peter Robin; Baum, Daniel; Garrison, Laura; Krueger, Robert
    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.
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    Interaction in Narrative Medical Visualization: Insights from a Case Study on Tumor Diseases
    (The Eurographics Association, 2025) Mlitzke, Sophie; Mittenentzwei, Sarah; Preim, Bernhard; Meuschke, Monique; Garrison, Laura; Krueger, Robert
    This paper examines how basic interaction techniques for medical data, such as clipping planes and manually adjusting the transparency of surfaces, commonly used in professional medical visualizations, can be adapted for medical stories intended for non-expert audiences. We implemented two case studies, involving liver and lung tumors. The goal was to effectively communicate critical aspects such as tumor size, position, and lymph node involvement to our target group. In a mixed-methods online study involving 26 participants, we examined how these techniques facilitate understanding and engagement. Results suggest that transparent surfaces and guided animations, followed by interactive exploration, were beneficial for communicating nested anatomical structures. While promising, these findings are preliminary and not conclusive; further studies with larger samples and real target audiences are needed to validate the effectiveness of these techniques. Our work provides initial design insights for making complex medical content more accessible through interactive storytelling.
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    Eurographics Workshop on Visual Computing for Biology and Medicine: Short Papers Frontmatter
    (The Eurographics Association, 2025) Garrison, Laura; Krueger, Robert; Garrison, Laura; Krueger, Robert
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    Mind Mapping Anatomical Illustrations: Pilot Evaluation of Paper- and Slide-Based Educational Tools
    (The Eurographics Association, 2025) Rodrigues, Margarida; Afonso, João D.; Lúcio, Inês; Proença, Luís; Mendes, José João; Rodrigues, Pedro; Raidou, Renata Georgia; Lopes, Daniel S.; Garrison, Laura; Krueger, Robert
    Anatomy is often taught using traditional tools such as PowerPoint slides, which typically feature medical illustrations crowded with colored labels but without a clear representation of how anatomical concepts are interconnected. This is known to overwhelm students and to hinder their ability to understand and retain complex anatomical relationships. In this work, we explore an alternative to traditional slide-based education through the use of physicalized mind maps crafted as paper-based tools that integrate color-coded diagrams with anatomical illustrations, here called paper anatomy maps. Specifically, we conducted co-design sessions with stakeholders to inform the design of the paper-based tool, and subsequently evaluated their potential to enhance engagement and short-term retention in dental students learning skull osteology. A user study involving 30 dental students was conducted to compare PowerPoint slides and paper anatomy maps. While both methods promoted short-term retention, the paper-based format was perceived more positively in terms of usability, cognitive workload, and engagement, suggesting that interactive, hands-on tools like paper anatomy maps can enrich students' anatomy learning experiences.
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    Microglia Cell Segmentation Using a Hand-crafted Method Capable of Handling High Noise Levels in Image Data
    (The Eurographics Association, 2025) Wimmer, Georg; Khan, Ibrahim; Bieler, Lara; Benedetti, Bruno; Couillard-Despres, Sebastien; Uhl, Andreas; Garrison, Laura; Krueger, Robert
    Microglia are the resident immune cells in the brain and spinal cord, playing a crucial role in various pathological processes. Accurate segmentation of microglia is the first and most critical step in the analysis of their morphology, which serves as a labelfree, primary indicator of microglial phenotype. In this work, we present a fully automated microglia segmentation method that is capable of reliably detecting and segmenting microglia from surrounding tissue, even under challenging conditions with substantial tissue-caused background noise in the image data. Our method incorporates several novel approaches, including a highly effective way to remove background noise while preserving microglial structures and an approach for filtering out microglial structures without an associated cell nucleus. We compared our microglia cell segmentation method with three well-known segmentation approaches reported in previous work on microglial morphology. The methods were applied to 20 fluorescence microscopy images of the spinal cord containing hundreds of microglia, for which a manually segmented ground truth segmentation has been obtained. We show that our proposed method clearly outperforms the previous methods.
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    Narrative Medical Visualization to Communicate Vision Restoration to Patients: A Case Study
    (The Eurographics Association, 2025) Budich, Beatrice; Preim, Bernhard; Sabel, Bernhard A.; Meuschke, Monique; Garrison, Laura; Krueger, Robert
    Narrative medical visualization aims to make complex medical information accessible to a broad audience by combining storytelling with visual techniques. This approach bridges the communication gap between clinicians and patients, promoting patient collaboration and long-term recovery. Understanding the concept of therapy and its significance fosters a sense of ownership and empowerment, leading to increased motivation and engagement. However, clinicians face the challenge of providing patients with educational materials that explain complex medical mechanisms in a way that patients can understand and relate to their lifestyle. This case study focuses on an animation video prototype that demonstrates a therapy concept for patients with low vision, aiming to ensure that patients are well-informed and motivated to engage in the treatment process. An initial evaluation with patients showed a positive experience with the supplemental material and added value to the consultant's explanation.
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    Exploring Feasibility of Seamless Multiscale Zooming in Genome Browsers
    (The Eurographics Association, 2025) Ståhlbom, Emilia; Molin, Jesper; Lundström, Claes; Ynnerman, Anders; Garrison, Laura; Krueger, Robert
    A central challenge when visualizing genomics data is the vast difference in the scales of interest. At a detailed level, structures around the size of 150 base pairs are studied. These are positioned throughout a genome that exceeds three billion base pairs. Surprisingly, the most prominently used genome browsers have limited multiscale navigation support. As an example, zooming is controlled by inputting coordinates or by clicking buttons. In this paper, we highlight seamless multiscale interaction as an opportunity for improvement in genomics data visualization. We developed a proof-of-concept system employing methods from interactive visualization of large-scale imagery. Our results show that genomics-specific challenges can be addressed and that context-preserving zooming in genomics is feasible. We argue that the multiscale capability is an essential usability requirement for the growing and broadening user base for genome browsers, a result of the rapidly increasing footprint of genomics in routine healthcare.