Now showing items 1-16 of 16

    • COMFIS - Comparative Visualization of Simulated Medical Flow Data 

      Meuschke, Monique; Voß, Samuel; Eulzer, Pepe; Janiga, Gabor; Arens, Christoph; Wickenhöfer, Ralph; Preim, Bernhard; Lawonn, Kai (The Eurographics Association, 2022)
      Simulations of human blood and airflow are playing an increasing role in personalized medicine. Comparing flow data of different treatment scenarios or before and after an intervention is important to assess treatment ...
    • Distance Visualizations for Vascular Structures in Desktop and VR: Overview and Implementation 

      Hombeck, Jan; Meuschke, Monique; Lieb, Simon; Lichtenberg, Nils; Datta, Rabi; Krone, Michael; Hansen, Christian; Preim, Bernhard; Lawonn, Kai (The Eurographics Association, 2022)
      The role of expressive surface visualizations in rendering vascular structures has seen an increased impact over the last years. Surface visualizations provide an overview of complex anatomical structures and support ...
    • Eurographics Workshop on Visual Computing for Biology and Medicine: Frontmatter 

      Renata G. Raidou; Björn Sommer; Torsten W. Kuhlen; Michael Krone; Thomas Schultz; Hsiang-Yun Wu (The Eurographics Association, 2022)
    • HistoContours: a Framework for Visual Annotation of Histopathology Whole Slide Images 

      Al-Thelaya, Khaled; Joad, Faaiz; Gilal, Nauman Ullah; Mifsud, William; Pintore, Giovanni; Gobbetti, Enrico; Agus, Marco; Schneider, Jens (The Eurographics Association, 2022)
      We present an end-to-end framework for histopathological analysis of whole slide images (WSIs). Our framework uses deep learning-based localization & classification of cell nuclei followed by spatial data aggregation to ...
    • Is there a Tornado in Alex's Blood Flow? A Case Study for Narrative Medical Visualization 

      Kleinau, Anna; Stupak, Evgenia; Mörth, Eric; Garrison, Laura A.; Mittenentzwei, Sarah; Smit, Noeska N.; Lawonn, Kai; Bruckner, Stefan; Gutberlet, Matthias; Preim, Bernhard; Meuschke, Monique (The Eurographics Association, 2022)
      Narrative visualization advantageously combines storytelling with new media formats and techniques, like interactivity, to create improved learning experiences. In medicine, it has the potential to improve patient understanding ...
    • Learning Anatomy through Shared Virtual Reality 

      Reyes-Cabrera, José Juan; Santana-Núñez, José Miguel; Trujillo-Pino, Agustín; Maynar, Manuel; Rodriguez-Florido, Miguel Angel (The Eurographics Association, 2022)
      Virtual reality (VR) is a powerful tool for educational purposes. In this work, we present a VR application for learning anatomy, focusing on the cardiac system in this early stage. Our application proposes that medical ...
    • Multi-modal 3D Image Registration Using Interactive Voxel Grid Deformation and Rendering 

      Richard, Thomas; Chastagnier, Yan; Szabo, Vivien; Chalard, Kevin; Summa, Brian; Thiery, Jean-Marc; Boubekeur, Tamy; Faraj, Noura (The Eurographics Association, 2022)
      We introduce a novel multi-modal 3D image registration framework based on 3D user-guided deformation of both volume's shape and intensity values. Being able to apply deformations in 3D gives access to a wide new range of ...
    • MuSIC: Multi-Sequential Interactive Co-Registration for Cancer Imaging Data based on Segmentation Masks 

      Eichner, Tanja; Mörth, Eric; Wagner-Larsen, Kari S.; Lura, Njål; Haldorsen, Ingfrid S.; Gröller, Eduard; Bruckner, Stefan; Smit, Noeska N. (The Eurographics Association, 2022)
      In gynecologic cancer imaging, multiple magnetic resonance imaging (MRI) sequences are acquired per patient to reveal different tissue characteristics. However, after image acquisition, the anatomical structures can be ...
    • Perceptual Evaluation of Common Line Variables for Displaying Uncertainty on Molecular Surfaces 

      Sterzik, Anna; Lichtenberg, Nils; Krone, Michael; Cunningham, Douglas W.; Lawonn, Kai (The Eurographics Association, 2022)
      Data are often subject to some degree of uncertainty, whether aleatory or epistemic. This applies both to experimental data acquired with sensors as well as to simulation data. Displaying these data and their uncertainty ...
    • Polyp-Cavity Segmentation of Cold-Water Corals guided by Ambient Occlusion and Ambient Curvature 

      Schmitt, Benedikt; Titschack, Jürgen; Baum, Daniel (The Eurographics Association, 2022)
      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, ...
    • Predicting, Analyzing and Communicating Outcomes of COVID-19 Hospitalizations with Medical Images and Clinical Data 

      Stritzel, Oliver; Raidou, Renata Georgia (The Eurographics Association, 2022)
      We propose PACO, a visual analytics framework to support the prediction, analysis, and communication of COVID-19 hospitalization outcomes. Although several real-world data sets about COVID-19 are openly available, most of ...
    • A Stratification Matrix Viewer for Analysis of Neural Network Data 

      Harth, Philipp; Vohra, Sumit; Udvary, Daniel; Oberlaender, Marcel; Hege, Hans-Christian; Baum, Daniel (The Eurographics Association, 2022)
      The analysis of brain networks is central to neurobiological research. In this context the following tasks often arise: (1) understand the cellular composition of a reconstructed neural tissue volume to determine the nodes ...
    • Studying the Effect of Tissue Properties on Radiofrequency Ablation by Visual Simulation Ensemble Analysis 

      Heimes, Karl; Evers, Marina; Gerrits, Tim; Gyawali, Sandeep; Sinden, David; Preusser, Tobias; Linsen, Lars (The Eurographics Association, 2022)
      Radiofrequency ablation is a minimally invasive, needle-based medical treatment to ablate tumors by heating due to absorption of radiofrequency electromagnetic waves. To ensure the complete target volume is destroyed, ...
    • Understanding Graph Convolutional Networks to detect Brain Lesions from Stroke 

      Iporre-Rivas, Ariel; Scheuermann, Gerik; Gillmann, Christina (The Eurographics Association, 2022)
      Brain lesions derived from stroke episodes can result in disabilities for a patient. Therefore, the segmentation of brain lesions is an important task in neurology. Recently this task has been mainly tackled by machine ...
    • Understanding the Impact of Statistical and Machine Learning Choices on Predictive Models for Radiotherapy 

      Böröndy, Ádám; Furmanová, Katarína; Raidou, Renata Georgia (The Eurographics Association, 2022)
      During radiotherapy (RT) planning, an accurate description of the location and shape of the pelvic organs is a critical factor for the successful treatment of the patient. Yet, during treatment, the pelvis anatomy may ...
    • Visual Analytics to Assess Deep Learning Models for Cross-Modal Brain Tumor Segmentation 

      Magg, Caroline; Raidou, Renata Georgia (The Eurographics Association, 2022)
      Accurate delineations of anatomically relevant structures are required for cancer treatment planning. Despite its accuracy, manual labeling is time-consuming and tedious-hence, the potential of automatic approaches, such ...