Refine
Year of publication
Document Type
- In Proceedings (151)
- Article (123)
- ZIB-Report (30)
- Book chapter (15)
- Other (14)
- In Collection (9)
- Book (3)
- Poster (3)
Keywords
- DVR (2)
- 3D neural network (1)
- Cultural Heritage (1)
- DNA (1)
- Dense connectome (1)
- GPU acceleration (1)
- Gaussian Process (1)
- HCI (1)
- Interaction Techniques (1)
- Kendall (1)
Institute
- Visual Data Analysis (348) (remove)
Neue Bilder für die Medizin?
(2005)
Operieren im Medizin-Grid
(2002)
For medical diagnosis, visualization, and model-based therapy planning three-dimensional geometric reconstructions of individual anatomical structures are often indispensable. Computer-assisted, model-based planning procedures typically cover specific modifications of “virtual anatomy” as well as numeric simulations of associated phenomena, like e.g. mechanical loads, fluid dynamics, or diffusion processes, in order to evaluate a potential therapeutic outcome. Since internal anatomical structures cannot be measured optically or mechanically in vivo, three-dimensional reconstruction of tomographic image data remains the method of choice. In this work the process chain of individual anatomy reconstruction is described which consists of segmentation of medical image data, geometrical reconstruction of all relevant tissue interfaces, up to the generation of geometric approximations (boundary surfaces and volumetric meshes) of three-dimensional anatomy being suited for finite element analysis. All results presented herein are generated with amira ® – a highly interactive software system for 3D data analysis, visualization and geometry reconstruction.
Maxillofacial surgery planning with 3D soft tissue prediction - modeling, planning, simulation
(2005)
Intakte Gelenke sind eine Voraussetzung für das Funktionieren des Skeletts und die Mobilität im Lebensalltag. Ein gesunder Bewegungsapparat ist die Grundlage für die Funktionsfähigkeit des Herz-Kreislauf-Systems wie auch der Immunabwehr. Bewegungs- und Physiotherapie sowie verschiedene Formen der Patientenaktivität stellen essenzielle klinische Ansätze in der Behandlung von neurodegenerativen Erkrankungen, Schlaganfall, Diabetes und Krebs dar. Kommt es zu degenerativen Veränderungen von Gelenken, bedeutet dies eine wesentliche Beeinträchtigung der Mobilität. Nächtliche Schmerzen und Schlafstörungen treten in fortgeschrittenen Stadien auf und sind besonders belastend. Arthrose wird auch als degenerative Gelenkerkrankung bezeichnet. Sie geht mit Veränderungen in der Struktur und Zusammensetzung des Gelenkknorpels wie auch des verkalkten Knorpels, der subchondralen Kortikalis, der subchondralen Spongiosa, des Meniskus, der Gelenkkapsel und der Synovialis einher, was schließlich zur Degeneration dieser Gewebe führt, aus denen sich die Synovialgelenke zusammensetzen.
Intact joints are necessary for skeletal function and mobility in daily life. A healthy musculoskeletal system is the basis for a functional cardiovascular
system as well as an intact immune system. Locomotion, physiotherapy, and various forms of patient activity are essential clinical therapies used in the treatment of neurodegeneration, stroke, diabetes, and cancer. Mobility is substantially impaired with degeneration of joints and, in advanced stages, nighttime pain and sleep disturbance are particularly cumbersome.
Osteoarthritis (OA) is also known as degenerative joint disease. OA involves structural and compositional changes in the articular cartilage, as well as in the calcified cartilage, subchondral cortical bone, subchondral cancellous bone, meniscus, joint capsular tissue, and synovium; which eventually lead to degeneration of these tissues comprising synovial joints.
Radiologists from all application areas are trained to read slice-based visualizations of 3D medical image data. Despite the numerous
examples of sophisticated three-dimensional renderings, especially all variants of direct volume rendering, such methods are
often considered not very useful by radiologists who prefer slice-based visualization. Just recently there have been attempts to bridge this
gap between 2D and 3D renderings. These attempts include specialized techniques for volume picking that result in repositioning slices.
In this paper, we present a new volume picking technique that, in contrast to previous work, does not require pre-segmented data or metadata. The positions picked by our method are solely based on the data itself, the transfer function and,
most importantly, on the way the volumetric rendering is perceived by viewers. To demonstrate the usefulness of the proposed method
we apply it for automatically
repositioning slices in an abdominal MRI
scan, a data set from a flow simulation and a number of other volumetric scalar fields. Furthermore we discuss how the method can be implemented in combination with various different volumetric rendering techniques.
In this paper we describe VisiTrace, a novel technique to
draw 3D lines in 3D volume rendered images. It allows to
draw strokes in the 2D space of the screen to produce 3D
lines that run on top or in the center of structures actually
visible in the volume rendering. It can handle structures
that only shortly occlude the structure that has been visible at the starting point of the stroke and is able to ignore
such structures. For this purpose a shortest path algorithm
finding the optimal curve in a specially designed graph
data structure is employed. We demonstrate the usefulness of the technique by applying it to MRI data from
medicine and engineering, and show how the method can
be used to mark or analyze structures in the example data
sets, and to automatically obtain good views toward the
selected structures.
We present the first general scheme to describe all four types of characteristic curves of flow fields – stream, path, streak, and time lines – as tangent curves of a derived vector field. Thus, all these lines can be obtained by a simple integration of an autonomous ODE system. Our approach draws on the principal ideas of the recently introduced tangent curve description of streak lines. We provide the first description of time lines as tangent curves of a derived vector field, which could previously only be constructed in a geometric manner. Furthermore, our scheme gives rise to new types of curves. In particular, we introduce advected stream lines as a parameter-free variant of the time line metaphor. With our novel mathematical description of characteristic curves, a large number of feature extraction and analysis tools becomes available for all types of characteristic curves, which were previously only available for stream and path lines. We will highlight some of these possible applications including the computation of time line curvature fields and the extraction of cores of swirling advected stream lines.
Die 3D-Wasserscheidentransformation auf Graphenebene - eine Anwendung für die Hyperthermieplannung
(1997)
Smoke Surfaces: An Interactive Flow Visualization Technique Inspired by Real-World Flow Experiments
(2008)
In 2004, a team of researchers realized a semi-immersive interactive gallery installation, visualizing an 1834 Mediterranean garden, introduced as “italienisches Kunststück” (Italian legerdemain) by Peter Joseph Lenné. The park was originally realized on the grounds of Schloss Sanssouci in Potsdam, Germany. The installation centered on highly detailed renderings of hundreds of plants projected upon a panoramic display. Interactivity was expressed with a tangible interface which (while presently dated) we believe remains without near-precedent then or since. We present the installation (experienced by roughly 20,000 visitors), focusing on the interaction aspects. We introduce new book and table/door-format mockups. Drawing upon a heuristic of the scientist-philosopher Freeman Dyson, we consider grounded future prospect variations in the contexts of 2018, 2032, and 2202. We see this exercise as prospectively generalizing to a variety of similar and widely diverse application domains.
The neurons in the cerebral cortex are not randomly interconnected. This specificity in wiring can result from synapse formation mechanisms that connect neurons depending on their electrical activity and genetically defined identity. Here, we report that the morphological properties of the neurons provide an additional prominent source by which wiring specificity emerges in cortical networks. This morphologically determined wiring specificity reflects similarities between the neurons’ axo-dendritic projections patterns, the packing density and cellular diversity of the neuropil. The higher these three factors are the more recurrent is the topology of the network. Conversely, the lower these factors are the more feedforward is the network’s topology. These principles predict the empirically observed occurrences of clusters of synapses, cell type-specific connectivity patterns, and nonrandom network motifs. Thus, we demonstrate that wiring specificity emerges in the cerebral cortex at subcellular, cellular and network scales from the specific morphological properties of its neuronal constituents.
Saddle Connectors - An Approach to Visualizing the Topological Skeleton of Complex 3D Vector Fields
(2003)
This paper presents an algorithm called surfseek for selecting surfaces on the most visible features in direct volume rendering (DVR). The algorithm is based on a previously published technique (WYSIWYP) for picking 3D locations in DVR. The new algorithm projects a surface patch on the DVR image, consisting of multiple rays. For each ray the algorithm uses WYSIWYP or a variant of it to find the candidates for the most visible locations along the ray. Using these candidates the algorithm constructs a graph and computes a minimum cut on this graph. The minimum cut represents a visible and typically rather smooth surface. In the last step the selected surface is displayed. We provide examples for results using artificially generated and real-world data sets.
This paper presents an algorithm called surfseek for selecting surfaces
on the most visible features in direct volume rendering (DVR). The
algorithm is based on a previously published technique (WYSIWYP) for
picking 3D locations in DVR. The new algorithm projects a surface patch
on the DVR image, consisting of multiple rays. For each ray the algorithm
uses WYSIWYP or a variant of it to find the candidates for the
most visible locations along the ray. Using these candidates the algorithm
constructs a graph and computes a minimum cut on this graph. The minimum
cut represents a very visible but relatively smooth surface. In the
last step the selected surface is displayed. We provide examples for the
results in real-world dataset as well as in artificially generated datasets.
LIC on Surfaces
(1997)
We present a Visual Analytics approach that addresses the detection of interesting patterns in numerical time series, specifically from environmental sciences. Crucial for the detection of interesting temporal patterns are the time scale and the starting points one is looking at. Our approach makes no assumption about time scale and starting position of temporal patterns and consists of three main steps: an algorithm to compute statistical values for all possible time scales and starting positions of intervals, visual identification of potentially interesting patterns in a matrix visualization, and interactive exploration of detected patterns. We demonstrate the utility of this approach in two scientific scenarios and explain how it allowed scientists to gain new insight into the dynamics of environmental systems.
We consider the spectral proper orthogonal decomposition (SPOD) for experimental data of a turbulent swirling jet. This newly introduced method combines the advantages of spectral methods, such as Fourier decomposition or dynamic mode decomposition, with the energy-ranked proper orthogonal decomposition (POD). This poster visualizes how the modal energy spectrum transitions from the spectral purity of Fourier space to the sparsity of POD space. The transition is achieved by changing a single parameter – the width of the SPOD filter. Each dot in the 3D space corresponds to an SPOD mode pair, where the size and color indicates its spectral coherence. What we notice is that neither the Fourier nor the POD spectrum achieves a clear separation of the dynamic phenomena. Scanning through the graph from the front plane (Fourier) to the back plane (POD), we observe how three highly coherent SPOD modes emerge from the dispersed Fourier spectrum and later branch out into numerous POD modes.
The spatial properties of these three individual SPOD modes are displayed in the back of the graph using line integral convolution colored by vorticity. The first two modes correspond to single-helical global instabilities that are well known for these flows. Their coexistence, however, has not been observed until now. The third mode is of double- helical shape and has not been observed so far. For this considered data set and many others, the SPOD is superior in identification of coherent structures in turbulent flows. Hopefully, it gives access to new fluid dynamic phenomena and enriches the available methods.
In atmospheric sciences, sizes of data sets grow continuously due to increasing resolutions. A central task is the comparison of spatiotemporal fields, to assess different simulations and to compare simulations with observations. A significant information reduction is possible by focusing on geometric-topological features of the fields or on derived meteorological objects. Due to the huge size of the data sets, spatial features have to be extracted in time slices and traced over time. Fields with chaotic component, i.e. without 1:1 spatiotemporal correspondences, can be compared by looking upon statistics of feature properties. Feature extraction, however, requires a clear mathematical definition of the features - which many meteorological objects still lack. Traditionally, object extractions are often heuristic, defined only by implemented algorithms, and thus are not comparable. This work surveys our framework designed for efficient development of feature tracking methods and for testing new feature definitions. The framework supports well-established visualization practices and is being used by atmospheric researchers to diagnose and compare data.
In atmospheric sciences, sizes of data sets grow continuously due to increasing resolutions. A central task is the comparison of spatiotemporal fields, to assess different simulations and to compare simulations with observations. A significant information reduction is possible by focusing on geometric-topological features of the fields or on derived meteorological objects. Due to the huge size of the data sets, spatial features have to be extracted in time slices and traced over time. Fields with chaotic component, i.e. without 1:1 spatiotemporal correspondences, can be compared by looking upon statistics of feature properties. Feature extraction, however, requires a clear mathematical definition of the features – which many meteorological objects still lack. Traditionally, object extractions are often heuristic, defined only by implemented algorithms, and thus are not comparable. This work surveys our framework designed for efficient development of feature tracking methods and for testing new feature definitions. The framework supports well-established visualization practices and is being used by atmospheric researchers to diagnose and compare data.
Statistical methods to design computer experiments usually rely on a Gaussian process (GP) surrogate model, and typically aim at selecting design points (combinations of algorithmic and model parameters) that minimize the average prediction variance, or maximize the prediction accuracy for the hyperparameters of the GP surrogate.
In many applications, experiments have a tunable precision, in the sense that one software parameter controls the tradeoff between accuracy and computing time (e.g., mesh size in FEM simulations or number of Monte-Carlo samples).
We formulate the problem of allocating a budget of computing time over a finite set of candidate points for the goals mentioned above. This is a continuous optimization problem, which is moreover convex whenever the tradeoff function accuracy vs. computing time is concave.
On the other hand, using non-concave weight functions can help to identify sparse designs. In addition, using sparse kernel approximations drastically reduce the cost per iteration of the multiplicative weights updates that can be used to solve this problem.
This work introduces a novel streamline seeding technique based on dual streamlines that are orthogonal to the vector field, instead of tangential. The greedy algorithm presented here produces a net of orthogonal streamlines that is iteratively refined resulting in good domain coverage and a high degree of continuity and uniformity. The algorithm is easy to implement and efficient, and it naturally extends to curved surfaces.
Dual Streamline Seeding
(2009)
Probabilistic Marching Cubes
(2011)