• 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 ...

• 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 ...

• 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 ...

• 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 ...

• 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 ...

• 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 ...

• 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, ...

• 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 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 ...

• 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 ...

• 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 ...

• 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 ...

• 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 ...

• 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 ...

• 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)

• Projection Mapping for In-Situ Surgery Planning by the Example of DIEP Flap Breast Reconstruction 

  Martschinke, Jana; Klein, Vanessa; Kurth, Philipp; Engel, Klaus; Ludolph, Ingo; Hauck, Theresa; Horch, Raymund; Stamminger, Marc (The Eurographics Association, 2021)

  Nowadays, many surgical procedures require preoperative planning, mostly relying on data from 3D imaging techniques like computed tomography or magnetic resonance imaging. However, preoperative assessment of this data is ...

• AR-Assisted Craniotomy Planning for Tumour Resection 

  Wooning, Joost; Benmahdjoub, Mohamed; Walsum, Theo van; Marroquim, Ricardo (The Eurographics Association, 2021)

  Craniotomy is a procedure where neurosurgeons open the patient's skull to gain direct access to the brain. The craniotomy's position defines the access path from the skull surface to the tumour and, consequently, the healthy ...

• PerSleep: A Visual Analytics Approach for Performance Assessment of Sleep Staging Models 

  Garcia Caballero, Humberto S.; Corvò, Alberto; Meulen, Fokke van; Fonseca, Pedro; Overeem, Sebasitaan; Wijk, Jarke J. van; Westenberg, Michel A. (The Eurographics Association, 2021)

  Machine learning is becoming increasingly popular in the medical domain. In the near future, clinicians expect predictive models to support daily tasks such as diagnosis and prognostic analysis. For this reason, it is ...

• Multiple Scale Visualization of Electronic Health Records to Support Finding Medical Narratives 

  Linden, Sanne van der; Wijk, Jarke J. van; Funk, Mathias (The Eurographics Association, 2021)

  Electronic Health Records (EHRs) contain rich medical information about patients, possibly hundreds of notes, lab results, images and other information. Doctors can easily be overwhelmed by this wealth of information. For ...

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