328 Works

Defining Hatching in Art

Greg Philbrick & Craig S. Kaplan
We define hatching-a drawing technique-as rigorously as possible. A pure mathematical formulation or even a binary this-or-that definition is unreachable, but useful insights come from driving as close as we can. First we explain hatching's purposes. Then we define hatching as the use of patches: groups of roughly parallel curves that form flexible, simple patterns. After elaborating on this definition's parts, we briefly treat considerations for research in expressive rendering.

Evolutionary Pathlines for Blood Flow Exploration in Cerebral Aneurysms

Benjamin Behrendt, Wito Engelke, Philipp Berg, Oliver Beuing, Bernhard Preim, Ingrid Hotz & Sylvia Saalfeld
Blood flow simulations play an important role for the understanding of vascular diseases, such as aneurysms. However, analysis of the resulting flow patterns, especially comparisons across patient groups, are challenging. Typically, the hemodynamic analysis relies on trial and error inspection of the flow data based on pathline visualizations and surface renderings. Visualizing too many pathlines at once may obstruct interesting features, e.g., embedded vortices, whereas with too little pathlines, particularities such as flow characteristics in...

Distance Field Visualization and 2D Abstraction of Vessel Tree Structures with on-the-fly Parameterization

Nils Lichtenberg, Bastian Krayer, Christian Hansen, Stefan Müller & Kai Lawonn
In this paper, we make contributions to the visualization of vascular structures. Based on skeletal input data, we provide a combined 2D and implicit 3D visualization of vasculature, that is parameterized on-the-fly for illustrative visualization. We use an efficient algorithm that creates a distance field volume from triangles and extend it to handle skeletal tree data. Spheretracing this volume allows to visualize the vasculature in a flexible way, without the need to recompute the volume....

Interactive CPU-based Ray Tracing of Solvent Excluded Surfaces

Tobias Rau, Sebastian Zahn, Michael Krone, Guido Reina & Thomas Ertl
Depictions of molecular surfaces such as the Solvent Excluded Surface (SES) can provide crucial insight into functional molecular properties, such as the molecule's potential to react. The interactive visualization of single and multiple molecule surfaces is essential for the data analysis by domain experts. Nowadays, the SES can be rendered at high frame rates using shader-based ray casting on the GPU. However, rendering large molecules or larger molecule complexes requires large amounts of memory that...

Molecular Sombreros: Abstract Visualization of Binding Sites within Proteins

Karsten Schatz, Michael Krone, Tabea L. Bauer, Valerio Ferrario, Jürgen Pleiss & Thomas Ertl
We present a novel abstract visualization for the binding sites of proteins. Binding sites play an essential role in enzymatic reactions and are, thus, often investigated in structural biology. They are typically located within cavities. The shape and properties of the cavity influence whether and how easily a substrate can reach the active site where the reaction is triggered. Molecular surface visualizations can help to analyze the accessibility of binding sites, but are typically prone...

Hybrid Visualization of Protein-Lipid and Protein-Protein Interaction

Naif Alharbi, Michael Krone, Matthieu Chavent & Robert S. Laramee
In the Molecular Dynamics (MD) visualization literature, different approaches are utilized to study protein-lipid interactions (PLI) and protein-protein interaction (PPI) in decoupled contexts. However, the two types of interaction occur in the same space-time domain. It is beneficial to study the PLI and PPI in a unified context. Nevertheless, the simulation's size, length, and complexity increase the challenge of understanding the dynamic behavior. We propose a novel framework consisting of four linked views, a time-dependent...

The Vitruvian Baby: Interactive Reformation of Fetal Ultrasound Data to a T-Position

Eric Mörth, Renata Georgia Raidou, Ivan Viola & Noeska N. Smit
Three-dimensional (3D) ultrasound imaging and visualization is often used in medical diagnostics, especially in prenatal screening. Screening the development of the fetus is important to assess possible complications early on. State of the art approaches involve taking standardized measurements to compare them with standardized tables. The measurements are taken in a 2D slice view, where precise measurements can be difficult to acquire due to the fetal pose. Performing the analysis in a 3D view would...

HIFUpm: a Visual Environment to Plan and Monitor High Intensity Focused Ultrasound Treatments

Daniela Modena, Davide Bassano, Aaldert Elevelt, Marco Baragona, Peter A. J. Hilbers & Michel A. Westenberg
High Intensity Focused Ultrasound (HIFU) is a non invasive therapeutic method, which has been a subject of interest for the treatment of various kinds of tumors. Despite the numerous advantages, HIFU techniques do not reach the high delivery precision like other therapies (e.g., radiotherapy). For this reason, a correct therapy planning and monitoring in HIFU treatments remains a challenge. We propose HIFUpm, a visual analytics approach which enables the visualization of the HIFU simulation results,...

Robustness Evaluation of CFD Simulations to Mesh Deformation

Alexander Scheid-Rehder, Kai Lawonn & Monique Meuschke
CFD simulations are an increasingly important method for the non-invasive analysis of risk factors for aneurysm rupture. Their robustness, however, has to be examined more thoroughly before clinical use is possible. We present a novel framework that enables robustness evaluation of CFD simulation according to mesh deformation on patient-specific blood vessel geometry. Our tool offers a guided workflow to generate, run, and visualize OpenFOAM simulations, which significantly decreases the usual overhead of CFD simulations with...

Using Position-Based Dynamics for Simulating the Mitral Valve in a Decision Support System

Lars Walczak, Joachim Georgii, Lennart Tautz, Mathias Neugebauer, Isaac Wamala, Simon Sündermann, Volkmar Falk & Anja Hennemuth
In mitral valve interventions, surgeons have to select an optimal combination of techniques for every patient. Especially less experienced physicians would benefit from decision support for this process. To support the visual analysis of the patientspecific valvular dynamics and an in-silico pre-intervention simulation of different therapy options, a real-time simulation of the mitral valve is needed, especially for the use in a time-constrained clinical environment. We develop a simplified model of the mitral valve and...

InkVis: A High-Particle-Count Approach for Visualization of Phase-Contrast Magnetic Resonance Imaging Data

Niels H. L. C. De Hoon, Kai Lawonn, Andrei C. Jalba, Elmar Eisemann & Anna Vilanova
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...

Medical Animations: A Survey and a Research Agenda

Bernhard Preim & Monique Meuschke
Animation is a potentially powerful instrument to convey complex information with movements, smooth transitions between different states that employ the strong human capabilities to perceive and interpret motion. Animation is a natural choice to display time-dependent data where the dynamic nature of the data is mapped to a kind of video (temporal animation). Clipping planes may be smoothly translated and object transparency adapted to control visibility and further support emphasis of spatial relations, e.g. around...

Visual Analytics in Digital Pathology: Challenges and Opportunities

Alberto Corvò, Michel A. Westenberg, Reinhold Wimberger-Friedl, Stephan Fromme, Michel M. R. Peeters, Marc A. Van Driel & Jarke J. Van Wijk
The advances in high-throughput digitization, digital pathology systems, and quantitative image analysis opened new horizons in pathology. The diagnostic work of the pathologists and their role is likely to be augmented with computer-assistance and more quantitative information at hand. The recent success of artificial intelligence (AI) and computer vision methods demonstrated that in the coming years machines will support pathologists in typically tedious and highly subjective tasks and also in better patient stratification. In spite...

Layer-Aware iOCT Volume Rendering for Retinal Surgery

Jakob Weiss, Ulrich Eck, Muhamad Ali Nasseri, Mathias Maier, Abouzar Eslami & Nassir Navab
Retinal microsurgery is one of the most challenging types of surgery, yet in practice, intraoperative digital assistance is rare. The introduction of fast, microscope integrated Optical Coherence Tomography (iOCT) has enabled intraoperative imaging of subsurface structures. However, effective intraoperative visualization of this data poses a challenging problem both in terms of performance and engineering as well as for creating easily interpretable visualizations of this data. Most existing research focuses on visualization of diagnostic OCT data...

Interactive Exploded Views for Molecular Structures

Maximilian Sbardellati, Haichao Miao, Hsiang-Yun Wu, Eduard Gröller, Ivan Barisic & Ivan Viola
We propose an approach to interactively create exploded views of molecular structures with the goal to help domain experts in their design process and provide them with a meaningful visual representation of component relationships. Exploded views are excellently suited to manage visual occlusion of structure components, which is one of the main challenges when visualizing complex 3D data. In this paper, we discuss four key parameters of an exploded view: explosion distance, direction, order, and...

DockVis: Visual Analysis of Molecular Docking Data

Katarína Furmanová, Barbora Kozlíková, Vojtěch Vonásek & Jan Byška
Molecular docking is one of the key mechanisms for predicting possible interactions between ligands and proteins. This highly complex task can be simulated by several software tools, providing the biochemists with possible ligand trajectories, which have to be subsequently explored and evaluated for their biochemical relevance. This paper focuses on aiding this exploration process by introducing DockVis visual analysis tool. DockVis operates primarily with the multivariate output data from one of the latest available tools...

MedUse: A Visual Analysis Tool for Medication Use Data in the ABCD Study

Hauke Bartsch, Laura Garrison, Stefan Bruckner, Ariel Wang, Susan F. Tapert & Renate Grüner
The RxNorm vocabulary is a yearly-published biomedical resource providing normalized names for medications. It is used to capture medication use in the Adolescent Brain Cognitive Development (ABCD) study, an active and publicly available longitudinal research study following 11,800 children over 10 years. In this work, we present medUse, a visual tool allowing researchers to explore and analyze the relationship of drug category to cognitive or imaging derived measures using ABCD study data. Our tool provides...

preha: Establishing Precision Rehabilitation with Visual Analytics

Georg Bernold, Kresimir Matkovic, Eduard Gröller & Renata Georgia Raidou
This design study paper describes preha, a novel visual analytics application in the field of in-patient rehabilitation. We conducted extensive interviews with the intended users, i.e., engineers and clinical rehabilitation experts, to determine specific requirements of their analytical process.We identified nine tasks, for which suitable solutions have been designed and developed in the flexible environment of kibana. Our application is used to analyze existing rehabilitation data from a large cohort of 46,000 patients, and it...

A Visual Analytics Approach for Patient Stratification and Biomarker Discovery

Shiva Alemzadeh, Florian Kromp, Bernhard Preim, Sabine Taschner-Mandl & Katja Bühler
We introduce discoVA as a visual analytics tool for the refinement of risk stratification of cancer patients and biomarker discovery. Currently, tools for the joint analysis of multiple biological and clinical information in this field are insufficient or lacking. Our tool fills this gap by enabling bio-medical experts to explore datasets of cancer patient cohorts. By using multiple coordinated visualization techniques, nested visual queries on various data types can be performed to generate/prove a hypothesis...

Pelvis Runner: Visualizing Pelvic Organ Variability in a Cohort of Radiotherapy Patients

Nicolas Grossmann, Oscar Casares-Magaz, Ludvig Paul Muren, Vitali Moiseenko, John P. Einck, Eduard Gröller & Renata Georgia Raidou
In radiation therapy, anatomical changes in the patient might lead to deviations between the planned and delivered dose- including inadequate tumor coverage, and overradiation of healthy tissues. Exploring and analyzing anatomical changes throughout the entire treatment period can help clinical researchers to design appropriate treatment strategies, while identifying patients that are more prone to radiation-induced toxicity. We present the Pelvis Runner, a novel application for exploring the variability of segmented pelvic organs in multiple patients,...

Feasibility Study For Automatic Bird Tracking and Visualization from Time-Dependent Marine Radar Imagery

Florian Ganglberger & Katja Bühler
In recent years, radar technology has increasingly been used for the monitoring of bird migration. Marine radars are often utilized for this purpose because of their wide accessibility, range, and resolution. They allow the tracking of birds even at night-when most bird migration takes place-over extended periods of time. This creates a wealth of radar images, for which manual annotation of bird tracks is not feasible. We propose a tool for automatic bird tracking and...

A Visual Environment for Hypothesis Formation and Reasoning in Studies with fMRI and Multivariate Clinical Data

Daniel Jönsson, Albin Bergström, Camilla Forsell, Rozalyn Simon, Maria Engström, Anders Ynnerman & Ingrid Hotz
We present an interactive visual environment for linked analysis of brain imaging and clinical measurements. The environment is developed in an iterative participatory design process involving neuroscientists investigating the causes of brain-related complex diseases. The hypotheses formation process about correlations between active brain regions and physiological or psychological factors in studies with hundreds of subjects is a central part of the investigation. Observing the reasoning patterns during hypotheses formation, we concluded that while existing tools...

Interactive Formation of Statistical Hypotheses in Diffusion Tensor Imaging

Amin Abbasloo, Vitalis Wiens, Tobias Schmidt-Wilcke, Pia Sundgren, Reinhard Klein & Thomas Schultz
When Diffusion Tensor Imaging (DTI) is used in clinical studies, statistical hypothesis testing is the standard approach to establish significant differences between groups, such as patients and healthy controls. However, diffusion tensors contain six degrees of freedom, and the most commonly used univariate tests reduce them to a single scalar, such as Fractional Anisotropy. Multivariate tests that account for the full tensor information have been developed, but have not been widely adopted in practice. Based...

Semantic Segmentation of Brain Tumors in MRI Data Without any Labels

Leon Weninger, Imke Krauhausen & Dorit Merhof
Brain MR images are one of the most important instruments for diagnosing neurological disorders such as tumors, infections or trauma. In particular, grade I-IV brain tumors are a well-studied subject for supervised deep learning approaches. However, for a clinical use of these approaches, a very large annotated database that covers all of the occurring variance is necessary. As MR scanners are not quantitative, it is unclear how good supervised approaches, trained on a specific database,...

A Web-based Application for the Visual Exploration of Colon Morphology Data

Jan Males, Eva Monclús, Jose Díaz & Pere-Pau Vázquez
The colon is an organ whose constant motility poses difficulties to its analysis. Although morphological data can be successfully extracted from Computational Tomography, its radiative nature makes it only indicated for patients with disorders. Only recently, acquisition techniques that rely on the use of Magnetic Resonance Imaging have matured enough to enable the generation of morphological colon data of healthy patients without preparation (i. e. administration of drugs or contrast agents). As a result, a...

Registration Year

  • 2019

Resource Types

  • Text