Here you can find an overview of our current research topics. There is also a list of awards of the visualization group available: go to awards page.

The genesis and progression of cardiovascular diseases (CVDs) depend on various factors. A better comprehension of patient-specific blood flow hemodynamics has great potential to increase their diagnosis, support treatment decision-making and provide a realistic forecast of such pathologies, facilitating a better implementation of preventative measures. Four-dimensional phase-contrast magnetic resonance imaging (4D PC-MRI) gained increasing importance and clinical attention in recent years. It is a non-invasive imaging modality that allows for time-resolved, three-dimensional measurement of blood flow information. The resulting 4D grid data, which contain vectors that represent the blood flow direction and velocity, are of limited spatio-temporal resolution and suffer from multiple artifacts, making complex image processing methods a prerequisite. Qualitative data analysis aims to depict the course of the blood flow with emphasis on specific flow patterns, such as vortex flow, which can be an indicator for different cardiovascular diseases. For this purpose, flow visualization techniques can be adapted to the cardiac context. Quantitative data analysis facilitates assessment of, e.g., the cardiac function by evaluating stroke volumes, heart valve performances by evaluating percentaged back flows, and fluid-vessel wall interactions by evaluating wall shear stress.

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The “Virtual Anatomy” project develops and tests innovative concepts to modernize anatomy education. For example, the body donors that are used by medical students for preparation training are scanned in high resolution such that the preparation can also be simulated virtually. While the body donors can only be used for a limited time, the virtual models are basically always available. One of the practical research questions is how to directly integrate the viewing and analysis of 3D models into the curriculum of the anatomy education.

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The cost pressure on rehabilitation hospitals results in stroke patients being released from hospital after 3-4 weeks and having further therapy with occupational therapists and neuropsychologists in private practice. However, under current conditions, the treatment intensity that is necessary for an efficient follow-up therapy is not further ensured after rehabilitation hospital discharge. To achieve therapeutic effects, the initiated therapy must be continued by intensive and preferably daily training.

This research project aims at the development of a system for the therapy of cognitive disorders for patients after stroke in home training. For this purpose, user interfaces with new interaction and visualization techniques shall be developed. Furthermore, studies shall validate whether reward and motivation techniques from computer games can be transferred to the new therapy software. For example, one element of the motivation and reward strategy is the suitable illustration of patient’s performance data.

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Cerebral aneurysms show a high prevalence in the western population, while their annual risk of rupture is below 1%. The bleeding caused by a rupture of such an aneurysms can have fatal consequences, but the treatment procedure itself is risky and can lead to severe complications.

Therefore, assessing the risk of rupture is vital to devise an optimal, patient-specific treatment plan – especially for patients with multiple aneurysms that may require multiple treatment sessions. The goal of this project is to develop and evaluate visualization techniques that support physicians with treatment decisions in such cases.

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Large-scale longitudinal epidemiological studies investigate groups of people with common characteristics or experiences (a cohort) including socio-demographic and biological factors. Their goal is the characterization of health by identifying risk factors and their relations to diseases and the indication of a per subject risk of developing a disease. Carried out in waves over many years, they comprise thousands of individuals and ten thousands of variables. Cohort studies most recently also medical acquire image data. New Visual Analytics methods are developed as part of this project to support hypotheses validation and generation with respect to risk factors, inter-relations and relations A major goal is the visualization of inter- and intra-group statistical variance in organ shape.

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In traditional illustrations, many well established techniques exist to communicate information. Their advantages consist in enhancing important information while unimportant information are suppressed. The aim of this project is to develop and evaluate such illustrative rendering techniques (like stippling, hatching, smart visibility). Our investigations are focused on applying these techniques in a medical context.

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Many illustrative techniques for visualizing medical volume data and derived segmentation information have been developed and refined. However, it is difficult to decide which techniques should be used for particular applications, how they should be combined, which parameter adjustment achieve the best information transfer or how 2D and 3D displays influence the visualization perception and guide the users attention. This project investigates experimental studies to analyze illustrative visualization techniques used in 3D medical visualizations. We focus on the study design and try to adapt psychological theories and study concepts to complex 3D medical visualizations and techniques to analyze their benefit.

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In Toponomics, the function protein pattern in cells or tissue (the toponome) is imaged and analyzed for applications in toxicology, drug development and patient-drug-interaction. The most advanced imaging technique is robot-driven multi-parameter fluorescence microscopy. This technique is capable of co-mapping hundreds of proteins and their distribution and assembly in protein clusters across a cell or tissue sample. The imaging results in complex multi-parameter data composed of one slice or a 3D volume per protein affinity reagent. The goal of this project is to develop an interactive visual analysis framework which supports the biologist in evaluating the data.

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The aim of this project is to investigate the characteristics of blood flow in cerebral aneurysms. We focus on how new kinds endovasculare treatment can be used to influence the flow and decrease the risk for the patient. We deal with extraction, visualization and comparison of complex morphological information and flow features.

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The research project for the visualization of vessels covers different research areas, e.g., the visualization of intravascular image data and model-based vessel visualization techniques. The intravascular imaging includes optical coherence tomography and intravascular ultrasound. The obtained medical image data provide valueable information about the vessel wall and its morphology which play an important role for diagnosis and evaluation of cardiovascular diseases like atherosclerotic plaque. Furthermore, special techniques to enable blood flow simulations and new projection-based techniques, that improve the conventional CPR views, were developed. Previous projects cover direct volume rendering techniques and transfer function adaptions as well as the vessel visualization with implicit surfaces.

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In this project we develop facilities to create medical animations for intervention planning as well as for educational purposes. We also discuss the enhancement of interactive explorations with animations generated on the fly.

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The aim of this project consists in developing methods for image analysis, visualization, and exploration of ENT and liver surgery planning. We focus on simulation of endoscopic intervention due to a user-driven navigation, usage of illustrative rendering techniques and model-based image analsysis

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Surface models from medical image data typically suffer from artifacts such as staircases and terraces. Our goal is the (automated) generation of accurate and high quality surface models for surgical applications as well as simulations. The resulting surface models are evaluated regarding accuracy, smoothness, triangle quality (skewness), mesh resolution and homogeneity. The mesh generation process is focuses on image data preprocessing as well as postprocessing of the surface meshes (smoothing, remeshing, decimation).

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The efficient segmentation of anatomical and pathological structures in medical datasets is a prerequisite for various approaches to computer-supported therapy planning. This project is aimed at the model-based segmentation of anatomical structures from CT datasets using Stable 3D Mass-Spring Models (SMSM). Our long-term goal is to provide a general construction kit of elementary model-components which can be composed to build segmentation models for new structures easily.

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Minimally invasive endoscopic procedures are gaining importance, since they lead to a reduced trauma and hospitalization duration. Virtual endoscopy systems have been developed in order to simulate these interventions either for training purposes or for planning an actual intervention based on the CT or MRI data of the patient. We focus on interactive systems, that allow to interactively explore hollow space organs and support the patient education, operation planing or diagnosis of diseases. These tasks can be supported through the use real-time rendering techniques.

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Perfusion data are dynamic medical image data which characterize the regional blood flow in tissue. We focus on the visualization and exploration of perfusion data for diagnostic purposes in three major application areas: ischemic stroke diagnosis, breast tumor diagnosis and the diagnosis of coronary heart disease.

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The demand on education in surgery increases and classical educational methods can not meet it adequately. Therefore web-based training systems are developed, which have to be concepted and developed using several didactical and conceptual methods to allow learners more efficient learning. For procurement of explicit and implicit expertise and to represent the enormous anatomic diversity dynamic visualizations of the patients data are preferable. Modern web applications based on HTML 5 and WebGL are suitable for these requirements.

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