Browsing by Author "Lawonn, Kai"

Now showing 1 - 9 of 9
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    Automatic Animations to Analyze Blood Flow Data
    (The Eurographics Association, 2021) Apilla, Vikram; Behrendt, Benjamin; Lawonn, Kai; Preim, Bernhard; Meuschke, Monique; Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas
    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.
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    Automatic Cutting and Flattening of Carotid Artery Geometries
    (The Eurographics Association, 2021) Eulzer, Pepe; Richter, Kevin; Meuschke, Monique; Hundertmark, Anna; Lawonn, Kai; ,; Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas
    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.
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    Clasping Trees - A Pipeline for Interactive Procedural Tree Generation
    (The Eurographics Association, 2022) Lieb, Simon J.; Klee, Nicolas; Lawonn, Kai; Bender, Jan; Botsch, Mario; Keim, Daniel A.
    Trees in computer games are important components of an immersive game world. Realistic trees adapt to the environment in terms of shape and growth. Manually adapting each tree to its immediate environment is time-consuming. Hence, we present a pipeline to procedurally generate trees. This pipeline's input consists of tree-parameters and mesh sets. Tree-parameters have a direct influence on the final appearance of the tree. Meshes are used to indicate the space of the tree crown and surface for roots. We provide an overview of the necessary methods for procedural tree generation. Our method allows game developers to integrate the pipeline directly into their game engine, skipping the process of importing and maintaining external 3D-models. We used the Space Colonization Algorithm to generate roots of trees on the surface of a set of meshes. For the crown generation, we use an extended Space Colonization Algorithm called Self Organizing Trees. To receive the combined surface and volume of a set of meshes, we voxelize the individual mesh and compose it into a single voxel grid. We introduce two novel optimization methods to further increase the usability of the generated trees. These optimization methods decrease the necessary triangle count of the final mesh. The resulting trees can be used for real-life applications, such as games.
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    A Fully Integrated Pipeline for Visual Carotid Morphology Analysis
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Eulzer, Pepe; Deylen, Fabienne von; Hsu, Wei-Chan; Wickenhöfer, Ralph; Klingner, Carsten M.; Lawonn, Kai; Bujack, Roxana; Archambault, Daniel; Schreck, Tobias
    Analyzing stenoses of the internal carotids - local constrictions of the artery - is a critical clinical task in cardiovascular disease treatment and prevention. For this purpose, we propose a self-contained pipeline for the visual analysis of carotid artery geometries. The only inputs are computed tomography angiography (CTA) scans, which are already recorded in clinical routine. We show how integrated model extraction and visualization can help to efficiently detect stenoses and we provide means for automatic, highly accurate stenosis degree computation. We directly connect multiple sophisticated processing stages, including a neural prediction network for lumen and plaque segmentation and automatic global diameter computation. We enable interactive and retrospective user control over the processing stages. Our aims are to increase user trust by making the underlying data validatable on the fly, to decrease adoption costs by minimizing external dependencies, and to optimize scalability by streamlining the data processing. We use interactive visualizations for data inspection and adaption to guide the user through the processing stages. The framework was developed and evaluated in close collaboration with radiologists and neurologists. It has been used to extract and analyze over 100 carotid bifurcation geometries and is built with a modular architecture, available as an extendable open-source platform.
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    InkVis: A High-Particle-Count Approach for Visualization of Phase-Contrast Magnetic Resonance Imaging Data
    (The Eurographics Association, 2019) de Hoon, Niels; Lawonn, Kai; Jalba, Andrei; Eisemann, Elmar; Vilanova, Anna; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Phase-Contrast Magnetic Resonance Imaging (PC-MRI) measures volumetric and time-varying blood flow data, unsurpassed in quality and completeness. Such blood-flow data have been shown to have the potential to improve both diagnosis and risk assessment of cardiovascular diseases (CVDs) uniquely. Typically PC-MRI data is visualized using stream- or pathlines. However, time-varying aspects of the data, e.g., vortex shedding, breakdown, and formation, are not sufficiently captured by these visualization techniques. Experimental flow visualization techniques introduce a visible medium, like smoke or dye, to visualize flow aspects including time-varying aspects. We propose a framework that mimics such experimental techniques by using a high number of particles. The framework offers great flexibility which allows for various visualization approaches. These include common traditional flow visualizations, but also streak visualizations to show the temporal aspects, and uncertainty visualizations. Moreover, these patient-specific measurements suffer from noise artifacts and a coarse resolution, causing uncertainty. Traditional flow visualizations neglect uncertainty and, therefore, may give a false sense of certainty, which can mislead the user yielding incorrect decisions. Previously, the domain experts had no means to visualize the effect of the uncertainty in the data. Our framework has been adopted by domain experts to visualize the vortices present in the sinuses of the aorta root showing the potential of the framework. Furthermore, an evaluation among domain experts indicated that having the option to visualize the uncertainty contributed to their confidence on the analysis.
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    Interactive Multimodal Imaging Visualization for Multiple Sclerosis Lesion Analysis
    (The Eurographics Association, 2021) Sugathan, Sherin; Bartsch, Hauke; Riemer, Frank; Grüner, Renate; Lawonn, Kai; Smit, Noeska N.; Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas
    Multiple Sclerosis (MS) is a brain disease that is diagnosed and monitored extensively through MRI scans. One of the criteria is the appearance of so-called brain lesions. The lesions show up on MRI scans as regions with elevated or reduced contrast compared to the surrounding healthy tissue. Understanding the complex interplay of contrast, location and shape in images from multiple modalities from 2D MRI slices is challenging. Advanced visualization of appearance- and location-related features of lesions would help researchers in defining better disease characterization through MS research. Since a permanent cure is not possible in MS and medication-based disease modification is a common treatment path, providing better visualizations would strengthen research which investigates the effect of white matter lesions. Here we present an advanced visualization solution that supports analysis from multiple imaging modalities acquired in a clinical routine examination. The solution holds potential for enabling researchers to have a more intuitive perception of lesion features. As an example for enhancing the analytic possibilities, we demonstrate the benefits of lesion projection using both Diffusion Tensor Imaging (DTI) and gradient-based techniques. This approach enables users to assess brain structures across individuals as the atlas-based analysis provides 3D anchoring and labeling of regions across a series of brain scans from the same participant and across different participants. The projections on the brain surface also enable researchers to conduct detailed studies on the relationship between cognitive disabilities and location of lesions. This allows researchers to correlate lesions to Brodmann areas and related brain functions. We realize the solutions in a prototype application that supports both DTI and structural data. A qualitative evaluation demonstrates that our approach supports MS researchers by providing new opportunities for MS research.
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    An Overview of Techniques for Egocentric Black Hole Visualization and Their Suitability for Planetarium Applications
    (The Eurographics Association, 2022) Hissbach, Anny-Marleen; Dick, Christian; Lawonn, Kai; Bender, Jan; Botsch, Mario; Keim, Daniel A.
    The visualization of black holes is used in science communication to educate people about our universe and concepts of general relativity. Recent visualizations aim to depict black holes in realtime, overcoming the challenge of efficient general relativistic ray tracing. In this state-of-the-art report, we provide the first overview of existing works about egocentric black hole visualization that generate images targeted at general audiences. We focus on Schwarzschild and Kerr black holes and discuss current methods to depict the distortion of background panoramas, point-shaped stars, nearby objects, and accretion disks. Approaches to realtime visualizations are highlighted. Furthermore, we present the implementation of a state-of-the-art black hole visualization in the planetarium software Uniview.
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    A Survey of Visual Analytics for Public Health
    (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Preim, Bernhard; Lawonn, Kai; Benes, Bedrich and Hauser, Helwig
    We describe visual analytics solutions aiming to support public health professionals, and thus, preventive measures. Prevention aims at advocating behaviour and policy changes likely to improve human health. Public health strives to limit the outbreak of acute diseases as well as the reduction of chronic diseases and injuries. For this purpose, data are collected to identify trends in human health, to derive hypotheses, e.g. related to risk factors, and to get insights in the data and the underlying phenomena. Most public health data have a temporal character. Moreover, the spatial character, e.g. spatial clustering of diseases, needs to be considered for decision‐making. Visual analytics techniques involve (subspace) clustering, interaction techniques to identify relevant subpopulations, e.g. being particularly vulnerable to diseases, imputation of missing values, visual queries as well as visualization and interaction techniques for spatio‐temporal data. We describe requirements, tasks and visual analytics techniques that are widely used in public health before going into detail with respect to applications. These include outbreak surveillance and epidemiology research, e.g. cancer epidemiology. We classify the solutions based on the visual analytics techniques employed. We also discuss gaps in the current state of the art and resulting research opportunities in a research agenda to advance visual analytics support in public health.
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    Vessel Maps: A Survey of Map-Like Visualizations of the Cardiovascular System
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Eulzer, Pepe; Meuschke, Monique; Mistelbauer, Gabriel; Lawonn, Kai; Bruckner, Stefan; Turkay, Cagatay; Vrotsou, Katerina
    Map-like visualizations of patient-specific cardiovascular structures have been applied in numerous medical application contexts. The term map-like alludes to the characteristics these depictions share with cartographic maps: they show the spatial relations of data attributes from a single perspective, they abstract the underlying data to increase legibility, and they facilitate tasks centered around overview, navigation, and comparison. A vast landscape of techniques exists to derive such maps from heterogeneous data spaces. Yet, they all target similar purposes within disease diagnostics, treatment, or research and they face coinciding challenges in mapping the spatial component of a treelike structure to a legible layout. In this report, we present a framing to unify these approaches. On the one hand, we provide a classification of the existing literature according to the data spaces such maps can be derived from. On the other hand, we view the approaches in light of the manifold requirements medical practitioners and researchers have in their efforts to combat the ever-growing burden of cardiovascular disease. Based on these two perspectives, we offer recommendations for the design of map-like visualizations of the cardiovascular system.