348 Works

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...

Colonic Content Assessment from MRI Imaging Using a Semi-automatic Approach

Victor Ceballos, Eva Monclús, Pere-Pau Vázquez, Álvaro Bendezú, Marianela Mego, Xavier Merino, Fernando Azpiroz & Isabel Navazo
The analysis of the morphology and content of the gut is necessary in order to achieve a better understanding of its metabolic and functional activity. Magnetic resonance imaging (MRI) has become an important imaging technique since it is able to visualize soft tissues in an undisturbed bowel using no ionizing radiation. In the last few years, MRI of gastrointestinal function has advanced substantially. However, few studies have focused on the colon, because the analysis of...

Multiparametric Magnetic Resonance Image Synthesis using Generative Adversarial Networks

Christoph Haarburger, Nicolas Horst, Daniel Truhn, Mirjam Broeckmann, Simone Schrading, Christiane Kuhl & Dorit Merhof
Generative adversarial networks have been shown to alleviate the problem of limited training data for supervised learning problems in medical image computing. However, most generative models for medical images focus on image-to-image translation rather than de novo image synthesis. In many clinical applications, image acquisition is multiparametric, i.e. includes contrast-enchanced or diffusion-weighted imaging. We present a generative adversarial network that synthesizes a sequence of temporally consistent contrast-enhanced breast MR image patches. Performance is evaluated quantitatively...

SpectraMosaic: An Exploratory Tool for the Interactive Visual Analysis of Magnetic Resonance Spectroscopy Data

Laura Garrison, Jakub Vašíček, Renate Grüner, Noeska N. Smit & Stefan Bruckner
Magnetic resonance spectroscopy (MRS) allows for assessment of tissue metabolite characteristics used often for early detection and treatment evaluation of brain-related pathologies. However, a steep learning curve for metabolite interpretation, paired with limited visualization tools, have constrained the more widespread adoption of MRS in clinical practice. In this design study, we collaborated with domain experts to design a novel visualization tool for the exploration of tissue metabolite concentration ratios in MRS clinical and research studies....

VCBM 2019: Frontmatter

Barbora Kozlíková & Renata Georgia Raidou

Narrowcasting for Stereoscopic Photospherical Cinemagraphy

Michael Cohen, Takato Iida & Rintaro Sato
We have developed an application which blurs the distinction between static and dynamic imagery in a stereoscopic omnidirectional browser. A ''cinemagraph'' is a living picture, interpolating between a still photo and a video. A stereo omnidirectional camera can capture stereographic contents. Combining such functionality yields a photospherical cinemagraph. Runtime control of activation fields allows selective alternation between frozen and animated scene elements. Narrowcasting, a user interface idiom for selective activation, is used to alternate between...

VR Sickness Reduction in Stereoscopic Video Streaming System 'TwinCam' for a Remote Experience

Ryunosuke Yagi, Toi Fujie, Tomohiro Amemiya, Michiteru Kitazaki, Vibol Yem & Yasushi Ikei
In the present paper, a method to present remote stereoscopic vision with decreased VR sickness is discussed. Our omnidirectional stereoscopic video streaming system (TwinCam) is described introducing the merit of the design. One of the important features is VR sickness reduction which we evaluated by assessing the simulator sickness questionnaire comparing it with conventional parallel cameras design. The result revealed that the TwinCam has significantly suppressed VR sickness from the conventional parallel cameras, at the...

System for Body Motion Capture While Moving in Large Area

Yusuke Yuasa, Hideki Tamura, Vibol Yem, Tomohiro Amemiya, Michiteru Kitazaki & Yasushi Ikei
Previous motion capture device such as OptiTrack has actively used. However, it is suitable to measure in a narrow space. We proposed a system to measure the body motion while walking in a large area. In the system we attached OptiTrack, Depth sensor and 9-axis sensor to a mobile vehicle. This paper reports the potential of our system.

Augmented Dodgeball AR Viewer for Spectators

Shota Azuma, Clara Hertzog, Sho Sakurai, Koichi Hirota & Takuya Nojima
These last few years many systems and methods have been developed to provide information to spectators about a sport game such as baseball, basketball, soccer, etc. Among them, Augmented Sport is one of the emerging area that intends to merge video game concept into physical sports. This project focuses on merging game elements such as Health Points (HP), Attack Power (AP) and Defense Power (DP) to improve enjoyment and variety of players. During Augmented Dodgeball...

Registration Year

  • 2019

Resource Types

  • Text