Four-dimensional phase-contrast magnetic resonance imaging (4D PC-MRI ) is a method to non-invasively acquire blood flow in the aorta. This flow is commonly visualized as path lines inside of the vessels. Direct volume rendering (DVR) uses a transfer function to directly render the dataset without needing a manual segmentation. Since the transfer function can be manipulated on the fly, DVR allows fast exploration of the dataset. Using a simple intensity-based transfer function, however, either the intravascular blood flow would be hidden behind the vessel's front side or the entire vessel has to be culled from the visualization. Therefore, we propose an automated mechanism that reveals the vessel anatomy by removing their front sides based on the viewing direction. This creates an effect similar to frontface culling on surface renderings. The visibility of focus objects inside the anatomy is guaranteed while spatial awareness is mostly maintained due to the presence of anatomical structures as context information. While we were able to confirm the effectiveness of our method in an interview with a collaborating radiologist, it still proved to be somewhat limited by the data quality and lack of a manual segmentation.

The video illustrates our pipeline for investigating vortices in simulations of cerebral aneurysm hemodynamics. The demonstration case is a giant aneurysm of the left internal carotid artery (ICA) at the origin of the ophtalmic artery. The corresponding hemodynamic data was generated by Juan R. Cebral. In a first step, vortex core line segments are extracted from time step t of the simulation data and continuous core lines are formed in an enhancement step. Then, streamlines are integrated from core line points. To reduce visual clutter, streamlines are grouped based on equilibrium points along the core lines. The groups may be optionally refined in a clustering step generating a more detailed visualization of the flow pattern, especially further off the core lines. Finally, group/cluster representatives are computed and integrated with other simulated or derived data in a visual summary. The aneurysm at hand contains three major vortices. Among them is a so-called embedded vortex. This type of vortex is characterized by a vortex layer swirling in one direction along the vortex core line, and a second vortex layer swirling in the opposite direction and enveloping the first. The video illustrates a smart visibility strategy supporting the investigation of flow in the presence of multiple vortices. In an overview visualization, the representatives of all vortices are displayed. As the user zooms in on a vortex, all other vortices gradually disappear. If the user continues to zoom in, the representatives of the vortex in focus also start to fade-out and its spherical glyphs gradually shrink to reveal the core line and facilitate an inspection of its velocity magnitude profile.

Abstract?In this paper we present illustrative visualization techniques for PET/CT datasets. PET/CT scanners acquire both PET and CT image data in order to combine functional metabolic information with structural anatomical information. Current visualization techniques mainly rely on 2D image fusion techniques to convey this combined information to physicians. We introduce an illustrative 3D visualization technique, specifically designed for use with PET/CT datasets. This allows the user to easily detect foci in the PET data and to localize these regions by providing anatomical contextual information from the CT data. Furthermore, we provide transfer function specifically designed for PET data that facilitates the investigation of interesting regions. Our technique allows users to get a quick overview of regions of interest and can be used in treatment planning, doctor-patient communication and interdisciplinary communication. We conducted a qualitative evaluation with medical experts to validate the utility of our method in clinical practice.

Sketching 2D Vessels and Vascular Diseases with Integrated Blood Flow

Overview of the 3D Clustering Visualization

We present a novel line drawing algorithm that illustrates surfaces in real-time to convey their shape. We use line integral convolution (LIC) and employ ambient occlusion for illustrative surface rendering. Furthermore, our method depicts salient regions based on the illumination gradient. Our method works on animated surfaces in a frame-coherent manner. Therefore, it yields an illustrative representation of time-dependent surfaces as no preprocessing step is needed. In this paper, the method is used to highlight the structure of molecular surfaces and to illustrate important surface features like cavities, channels, and pockets. The benefit of our method was evaluated with domain experts. We also demonstrate the applicability of our method to medical visualization.

The investigation of hemodynamic information for the assessment of cardiovascular diseases (CVDs) gained importance in recent years. Improved flow measuring modalities and computational fluid dynamics (CFD) simulations yield in reliable blood flow information. For a visual exploration of the flow information, domain experts are used to investigate the flow information combined with its enclosed vessel anatomy. Since the flow is spatially embedded in the surrounding vessel surface, occlusion problems have to be resolved. A visual reduction of the vessel surface that still provides important anatomical features is required. We accomplish this by applying an adaptive surface visualization inspired by the suggestive contour measure. Furthermore, an illustration is employed to highlight the animated pathlines and to emphasize nearby surface regions. Our approach combines several visualization techniques to improve the perception of surface shape and depth. Thereby, we ensure appropriate visibility of the embedded flow information, which can be depicted with established or advanced flow visualization techniques. We apply our approach to cerebral aneurysms and aortas with simulated and measured blood flow. An informal user feedback with nine domain experts, we confirm the advantages of our approach compared with existing methods, e.g. semi-transparent surface rendering. Additionally, we assessed the applicability and usefulness of the pathline animation with highlighting nearby surface regions.

The expressive visualization of (time-dependent) 3D blood flow along with the vessel wall is essential for understanding vascular diseases. However, the high complexity of the underlying flow data makes the exploration challenging. For the biomedical research, it is necessary to provide methods that allow for rapid flow comprehension, ideally by emphasizing relevant flow characteristics. Therefore, we present a fast approach that visualizes streamlines in a view-dependent way, while taking relevant flow features into consideration. For this, we adapt a well-established non-photorealistic rendering technique (suggestive contours) for surface meshes to streamline illustrations. The advantages of our approach are confirmed in an informal user feedback with domain experts, who were able to comprehend the overall flow behavior faster.

The blood flow in a saccular side-wall aneurysm has been simulated based on the vascular morphology extracted from patient-individual data. The resulting flow data is often visualized by a dense and cluttered set of streamlines. Clustering the streamlines and computing cluster representatives reduces visual clutter and exposes characteristic flow structures. The resulting flow summary benefits the assessment of aneurysmal hemodynamics.

Overview of the method

Miscellaneous Models

Overview of the method

AmniVis - A system for visual qualitative exploration of near-wall flow patterns in cerebral aneurysms.

The video presents the automatically extracted inflow jet and impingement zone of a steady flow dataset in a cerebral aneurysm. The extraction approach is based on the inflow streamlines seeded at the ostium and employs local streamline properties (e.g., curvature and distances to the aneurysm wall). Several visualization techniques depict both characteristics.

Sample video of realtime mesh smoothing with mouse movements mapped onto smoothing parameters.

Sample video of realtime mesh smoothing. Quality measures, such as local errors, volume preservation, and curvature are computed in realtime.

Sample video of realtime mesh smoothing. Parameter suggestions may be generated for patient-specific data based on only one parameter - the target smoothness.

This video presents the FlowLens concept, a visual exploration approach of blood flow data in cerebral aneurysms. Relevant hemodynamic attributes, e.g., wall shear stress or pressure, are grouped to focus-and-context pairs and assigned to three different spatial scopes (global, near-wall, aneurysm). A 2.5D lens shape is used to embed locally the visualization of the context attribute within the focus attribute.

We present a three-scope approach for qualitative visual exploration of blood flow data. The scopes include a global scope, an ostium scope and a local scope. They are related to anatomic features such as the centerline, the ostium or the central aneurysm axis. The exploration includes multi-parameter visualisations and specialized widgets.

Interactive, graph-based visual analysis of toponome data. This special kind of data depicts the location and topological distribution of proteins in a cell or tissue sample. The particular data shown in the video represents a probe containing lymphocytes. The visual analysis framework supports the biologist in detecting and understanding a cell's function protein patterns.

This video presents a new adaptive visualization technique of Cerebral Aneurysms with Embedded Blood Flow Information. It combines smart visibility techniques, depth cues, and line rendering. More flow perception is achieved in comparison to semi-transparent surface visualization of the enclosing aneurysm.

Example of locally adaptive mesh smoothing using a staircase-aware approach.

Example of locally adaptive mesh smoothing using a staircase-aware approach. The video shows the adjustment of different parameters.

This video presents an approach to automatically extract important landmarks and geometrically reconstruct the ostium. As shown, the ostium can be used to seperate the aneurysm from the parent vessel. It forms the basis for a variety of applications, e.g. feature-aware visualization or guided interaction.

An overview visualization for scalar values (in this case wall shear stress) mapped on the aneurysm surface.

Video illustrating the development and application of glyphs to encoding

Video showing the interactive visual analysis of a dataset from breast tumor

Video illustrating the integration of myocardial perfusion and ventricular as well as vascular anatomy of a patient suffering from atherosclerosis. (Data is courtesy of M. Fenchel, S. Miller and A. Seeger, Max Planck MR-center, University of Tübingen, Germany, S. Achenbach, Department of Radiology, University of Erlangen-Nürnberg, Germany, and SIEMENS Healthcare)