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Bildverarbeitung für die Medizin Workshop, BVM 2023

作者： Tummala, Pavan Hille, Georg Saalfeld, Sylvia Department of Simulation and Graphics Faculty of Computer Science University of Magdeburg Germany

ISBN: (纸本)9783658416560

Lung cancer represents one of the most common and lethal types of cancerous pathologies and lung nodules are an early indicator for pulmonary cancer. Hence, a precise and reliable segmentation of lung nodules could enhance early diagnosis and therapy and thus, increase patients’ survival rates. This work proposes a modified 3D-Res2Unet, combining an Unet-style neural network architecture with residual blocks and attention mechanisms. This network was tested on the publicly available LUNA16 CT dataset and achieved on average 91.27 ± 6.49 %. Therefore, the proposed method indicates state-of-the-art performance and could represent an important tool for early diagnosis of lung cancer. © 2023 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature.

关键词： computerized tomography

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WEB-ANEULYSIS: A Web-based Application for the Analysis of Aneurysm Data

WEB-ANEULYSIS: A Web-based Application for the Analysis of A...

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Bildverarbeitung für die Medizin Workshop, BVM 2023

作者： Preßler, Rebecca Meuschke, Monique Voigt, Henrik Lawonn, Kai Institute of Computer Science University of Jena Germany Department of Simulation and Graphics University of Magdeburg Germany

ISBN: (纸本)9783658416560

The analysis and treatment of cerebral aneurysms are important in neuroradiology. To support physicians in these tasks a desktop application for the visual analysis of aneurysm data called Aneulysis was developed. Because desktop applications complicate collaborative data exploration by physicians working at different locations,we present Web-Aneulysis, aweb-based version of Aneulysis written with the *** library. Especially the collaborative treatment planning is supported by our application. Therefore, Web-Aneulysis provides features for calculating morphological descriptors, positioning landmarks on the vessel surface, and deploying medical implants inside the vessel. We used Web-Aneulysis for the treatment planning of different cerebral aneurysm data sets and performed a qualitative evaluation together with two neuroradiologists. © 2023 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature.

关键词： Web services

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AI-based character generation for disease stories: a case study using epidemiological data to highlight preventable risk factors

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i-com 2025年第1期24卷 259-281页

作者： Mittenentzwei, Sarah Garrison, Laura A. Budich, Beatrice Lawonn, Kai Dockhorn, Alexander Preim, Bernhard Meuschke, Monique Department of Simulation and Graphics Otto-von-Guericke University of Magdeburg Universitätsplatz 2 Magdeburg39106 Germany Department of Informatics University of Bergen Thormøhlens Gate 55 Bergen5020 Norway Faculty of Mathematics and Computer Science University of Jena Ernst-Abbe-Platz 2 Jena07743 Germany Institute of Information Processing Leibniz University Hannover Welfengarten 1 Hannover30167 Germany

Data-driven storytelling has grown significantly, becoming prevalent in various fields, including healthcare. In medical narratives, characters are crucial for engaging audiences, making complex medical information accessible, and potentially influencing positive behavioral and lifestyle changes. However, designing characters that are both educational and relatable to effectively engage audiences is challenging. We propose a GenAI-assisted pipeline for character design in data-driven medical stories, utilizing Stable Diffusion, a deep learning text-to-image model, to transform data into visual character representations. This approach reduces the time and artistic skills required to create characters that reflect the underlying data. As a proof-of-concept, we generated and evaluated two characters in a crowd-sourced case study, assessing their authenticity to the underlying data and consistency over time. In a qualitative evaluation with four experts with knowledge in design and health communication, the characters were discussed regarding their quality and refinement opportunities. The characters effectively conveyed various aspects of the data, such as emotions, age, and body weight. However, generating multiple consistent images of the same character proved to be a significant challenge. This underscores a key issue in using generative AI for character creation: the limited control designers have over the output. © 2025 the author(s), published by De Gruyter, Berlin/Boston.

关键词： data-storytelling GenAI medicine healthcare character generation

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Virtual DSA Visualization of Simulated Blood Flow Data in Cerebral Aneurysms

Virtual DSA Visualization of Simulated Blood Flow Data in Ce...

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German Workshop on Medical Image Computing, 2022

作者： Preßler, Rebecca Lawonn, Kai Preim, Bernhard Meuschke, Monique Institute of Computer Science University of Jena Jena Germany Department of Simulation and Graphics University of Magdeburg Magdeburg Germany

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Weighting Attributes Based on the Greedy Algorithm Properties 28th

Weighting Attributes Based on the Greedy Algorithm Propertie...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Zielosko, Beata Stanczyk, Urszula Jablonski, Kamil University of Silesia in Katowice Institute of Computer Science Bedzinska 39 Sosnowiec41-200 Poland Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

Estimation of importance for considered features is an important issue for any knowledge exploration process and it can be executed by a variety of approaches. In the research reported in this study, the primary aim was the development of a methodology for creating attribute rankings. Based on the properties of the greedy algorithm for inducing decision rules, a new application of this algorithm has been proposed. Instead of constructing a single ordering of features, attributes were weighted multiple times. The input datasets were discretised with several algorithms representing supervised and unsupervised discretisation approaches. Each resulting discrete data variant was exploited to construct a ranking of attributes. The effectiveness of the obtained rankings was confirmed through a rule filtering process governed by weighted attributes. The methodology was applied to the stylometric task of authorship attribution. The experimental outcomes demonstrate the value of the proposed research method, as it generally led to improved predictions while taking into account a noticeably decreased sets of attributes and decision rules. © 2024 The Authors.

关键词： Consensus algorithm

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First Competition on Presentation Attack Detection on ID Card 18

First Competition on Presentation Attack Detection on ID Car...

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18th IEEE International Joint Conference on Biometrics, IJCB 2024

作者： Tapia, Juan E. Damer, Naser Busch, Christoph Espin, Juan M. Barrachina, Javier Rocamora, Alvaro S. Ocvirk, Krištof Alessio, Leon Batagelj, Borut Patwardhan, Sushrut Ramachandra, Raghavendra Mudgalgundurao, Raghavendra Raja, Kiran Schulz, Daniel Aravena, Carlos Da/sec-Biometrics and Internet Security Research Germany Fraunhofer Institute for Computer Graphics Research Igd Darmstadt Germany Tu Darmstadt Department of Computer Science Darmstadt Germany Facephi Company Spain University of Ljubljana Faculty of Computer and Information Science Ljubljana Slovenia Gjøvik Norway Santiago Chile

ISBN: (纸本)9798350364132

This paper summarises the Competition on Presentation Attack Detection on ID Cards (PAD-IDCard) held at the 2024 International Joint Conference on Biometrics (IJCB 2024). The competition attracted a total of ten registered teams, both from academia and industry. In the end, the participating teams submitted five valid submissions, with eight models to be evaluated by the organisers. The competition presented an independent assessment of current state-of-the-art algorithms. Today, no independent evaluation on cross-dataset is available;therefore, this work determined the state-of-the-art on ID cards. To reach this goal, a sequestered test set and baseline algorithms were used to evaluate and compare all the proposals. The sequestered test dataset contains ID cards from four different countries. In summary, a team that chose to be "Anonymous"reached the best average ranking results of 74.80%, followed very closely by the "IDVC"team with 77.65%. © 2024 IEEE.

关键词： Biometrics

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Automatic Animations to Analyze Blood Flow Data

Automatic Animations to Analyze Blood Flow Data

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2021 Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2021

作者： Apilla, V. Behrendt, B. Lawonn, K. Preim, B. Meuschke, M. Department of Simulation and Graphics University of Magdeburg Germany Institute of Computer Science University of Jena Germany

ISBN: (纸本)9783038681403

We present an approach for computing camera animations composed of optimal views to support the visual exploration of blood flow data using cerebral aneurysms as major example. Medical researchers are interested in hemodynamic parameters and vessel wall characteristics. The time-dependent character of blood flow data complicates the visual analysis. Our approach is modeled as an optimization problem to automatically determine camera paths during the cardiac cycle. These consist of optimal viewpoints showing regions with suspicious characteristics of wall- and flow-related parameters. This provides medical researchers with an efficient method of obtaining a fast overview of patient-specific blood flow data. © 2021 The Author(s) Eurographics Proceedings © 2021 The Eurographics Association.

关键词： Cameras

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Embryonic heart development as an immersive experience: Unveiling learning effects and influential factors in virtual learning environments

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computers in Biology and Medicine 2025年 187卷 109638-109638页

作者： Kunz, Matthias Schott, Danny Wunderling, Tom Halloul, Martin Hansen, Christian Albrecht, Anne Braun-Dullaeus, Rüdiger C. Otto von Guericke University Medical Faculty Department of Internal Medicine/Cardiology and Angiology Magdeburg Germany Otto von Guericke University Faculty of Computer Science Department of Simulation and Graphics Magdeburg Germany Otto von Guericke University Medical Faculty Institute of Anatomy Magdeburg Germany

As the quality and availability of Virtual Reality (VR) technologies improve, their potential applications in medical education, particularly VR Learning Environments (VRLEs), are increasingly explored. VRLEs offer a dynamic platform where educators and students can interact, access materials, and engage in learning beyond traditional classrooms. However, questions remain about their long-term learning effects and potential confounding factors. This study investigates these aspects through a VR application designed for teaching heart embryology. For this reason we conducted a user study with medical students in their early years of training (N = 143). Our findings reveal significant short-term and sustained learning outcomes two to four weeks following a single VR session. Importantly, these outcomes appear largely independent of users’ technical affinity and are minimally influenced by their immersion tendencies. Instead, the quality of the VRLE and its user experience emerge as critical factors. These results underscore the efficacy of well-designed VRLEs in higher education and highlight key areas for future development. © 2025 The Authors

关键词： Virtual environments

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Automatic Cutting and Flattening of Carotid Artery Geometries

Automatic Cutting and Flattening of Carotid Artery Geometrie...

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2021 Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2021

作者： Eulzer, P. Richter, K. Meuschke, M. Hundertmark, A. Lawonn, K. University of Jena Faculty of Mathematics and Computer Science Germany University of Koblenz-Landau Institute for Mathematics Germany University of Magdeburg Department of Simulation and Graphics Germany

ISBN: (纸本)9783038681403

We propose a novel method to cut and flatten vascular geometry that results in an intuitive mapping between the 3D and 2D domains. Our approach is fully automatic, and the sole input is the vessel geometry. We aim to simplify parameter analysis on vessel walls for research on vascular disease and computational hemodynamics. We present a use case for the flattening to aid efforts in investigating the pathophysiology of carotid stenoses (vessel constrictions that are a root cause of stroke). To achieve an intuitive mapping, we introduce the notion of natural vessel cuts. They remain on one side of vessel branches, meaning they adhere to the longitudinal direction and thus result in a comprehensible unfolding of the geometry. Vessel branches and endpoints are automatically detected, and a 2D layout configuration is found that retains the original branch layout. We employ a quasi-isometric surface parameterization to map the geometry to the 2D domain as a single patch. The flattened depiction resolves the need for tedious 3D interaction as the whole surface is visible at once. We found this overview particularly beneficial for exploring temporally resolved parameters. © 2021 The Author(s) Eurographics Proceedings © 2021 The Eurographics Association.

关键词： Geometry

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Towards Large-Scale Video-Based Highway Traffic Monitoring

Towards Large-Scale Video-Based Highway Traffic Monitoring

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International Conference on Intelligent Transportation

作者： Johannes Spoecklberger Jakub Micorek Horst Possegger Horst Bischof Faculty of Computer Science Institute of Computer Graphics and Vision (ICG) Graz University of Technology Graz Austria

Traffic safety on highways is supported by a variety of technical measures, including countless camera systems that are often only monitored by human operators. However, due to the sheer amount of data, safety monitoring and accident prevention are limited by human resources. In this paper, we present an efficient system capable of extracting accurate vehicle trajectories from the vast amount of video data generated by modern highway infrastructures. Our proposed system conveniently leverages bird's eye view transformations estimated from aerial data or street marker geometry to generate geo-localized trajectories. Utilizing existing infrastructure, we demonstrate that the central data for video-based highway traffic monitoring can be reliably extracted. Remarkably, this can be achieved solely relying on uncalibrated cameras and noisy video streams.

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