IEEE VIS Publication Dataset

We present improved subdivision and isosurface reconstruction algorithms for polygonizing implicit surfaces and performing accurate geometric operations. Our improved reconstruction algorithm uses directed distance fields (Kobbelt et al., 2001) to detect multiple intersections along an edge, separates them into components and reconstructs an isosurface locally within each components using the dual contouring algorithm (Ju et al., 2002). It can reconstruct thin features without creating handles and results in improved surface extraction from volumetric data. Our subdivision algorithm takes into account sharp features that arise from intersecting surfaces or Boolean operations and generates an adaptive grid such that each voxel has at most one sharp feature. The subdivision algorithm is combined with our improved reconstruction algorithm to compute accurate polygonization of Boolean combinations or offsets of complex primitives that faithfully reconstruct the sharp features. We have applied these algorithms to polygonize complex CAD models designed using thousands of Boolean operations on curved primitives.

Unstructured meshes are often used in simulations and imaging applications. They provide advanced flexibility in modeling abilities but are more difficult to manipulate and analyze than regular data. This work provides a novel approach for the analysis of unstructured meshes using feature-space clustering and feature-detection. Analyzing and revealing underlying structures in data involve operators on both spatial and functional domains. Slicing concentrates more on the spatial domain, while iso-surfacing or volume rendering concentrate more on the functional domain. Nevertheless, many times it is the combination of the two domains which provides real insight on the structure of the data. In this work, a combined feature-space is defined on top of unstructured meshes in order to search for structure in the data. A point in feature-space includes the spatial coordinates of the point in the mesh domain and all chosen attributes defined on the mesh. A distance measures between points in feature-space is defined enabling the utilization of clustering using the mean shift procedure (previously used for images) on unstructured meshes. Feature space analysis is shown to be useful for feature-extraction, for data exploration and partitioning.

Volume rendering is a flexible technique for visualizing dense 3D volumetric datasets. A central element of volume rendering is the conversion between data values and observable quantities such as color and opacity. This process is usually realized through the use of transfer functions that are precomputed and stored in lookup tables. For multidimensional transfer functions applied to multivariate data, these lookup tables become prohibitively large. We propose the direct evaluation of a particular type of transfer functions based on a sum of Gaussians. Because of their simple form (in terms of number of parameters), these functions and their analytic integrals along line segments can be evaluated efficiently on current graphics hardware, obviating the need for precomputed lookup tables. We have adopted these transfer functions because they are well suited for classification based on a unique combination of multiple data values that localize features in the transfer function domain. We apply this technique to the visualization of several multivariate datasets (CT, cryosection) that are difficult to classify and render accurately at interactive rates using traditional approaches.

Non-linear filtering is an important task for volume analysis. This paper presents hardware-based implementations of various non-linear filters for volume smoothing with edge preservation. The Cg high-level shading language is used in combination with latest PC consumer graphics hardware. Filtering is divided into pervertex and per-fragment stages. In both stages we propose techniques to increase the filtering performance. The vertex program pre-computes texture coordinates in order to address all contributing input samples of the operator mask. Thus additional computations are avoided in the fragment program. The presented fragment programs preserve cache coherence, exploit 4D vector arithmetic, and internal fixed point arithmetic to increase performance. We show the applicability of non-linear filters as part of a GPU-based segmentation pipeline. The resulting binary mask is compressed and decompressed in the graphics memory on-the-fly.

We present the first implementation of a volume ray casting algorithm for tetrahedral meshes running on off-the-shelf programmable graphics hardware. Our implementation avoids the memory transfer bottleneck of the graphics bus since the complete mesh data is stored in the local memory of the graphics adapter and all computations, in particular ray traversal and ray integration, are performed by the graphics processing unit. Analogously to other ray casting algorithms, our algorithm does not require an expensive cell sorting. Provided that the graphics adapter offers enough texture memory, our implementation performs comparable to the fastest published volume rendering algorithms for unstructured meshes. Our approach works with cyclic and/or non-convex meshes and supports early ray termination. Accurate ray integration is guaranteed by applying pre-integrated volume rendering. In order to achieve almost interactive modifications of transfer functions, we propose a new method for computing three-dimensional pre-integration tables.

In this paper we use advanced tensor visualization techniques to study 3D diffusion tensor MRI data of a heart. We use scalar and tensor glyph visualization methods to investigate the data and apply a moving least squares (MLS) fiber tracing method to recover and visualize the helical structure and the orientation of the heart muscle fibers.

We present a method to represent unstructured scalar fields at multiple levels of detail. Using a parallelizable classification algorithm to build a cluster hierarchy, we generate a multiresolution representation of a given volumetric scalar data set. The method uses principal component analysis (PCA) for cluster generation and a fitting technique based on radial basis functions (RBFs). Once the cluster hierarchy has been generated, we utilize a variety of techniques for extracting different levels of detail. The main strength of this work is its generality. Regardless of grid type, this method can be applied to any discrete scalar field representation, even one given as a "point cloud".

Numerical particle simulations and astronomical observations create huge data sets containing uncorrelated 3D points of varying size. These data sets cannot be visualized interactively by simply rendering millions of colored points for each frame. Therefore, in many visualization applications a scalar density corresponding to the point distribution is resampled on a regular grid for direct volume rendering. However, many fine details are usually lost for voxel resolutions which still allow interactive visualization on standard workstations. Since no surface geometry is associated with our data sets, the recently introduced point-based rendering algorithms cannot be applied as well. In this paper we propose to accelerate the visualization of scattered point data by a hierarchical data structure based on a PCA clustering procedure. By traversing this structure for each frame we can trade-off rendering speed vs. image quality. Our scheme also reduces memory consumption by using quantized relative coordinates and it allows for fast sorting of semi-transparent clusters. We analyze various software and hardware implementations of our renderer and demonstrate that we can now visualize data sets with tens of millions of points interactively with sub-pixel screen space error on current PC graphics hardware employing advanced vertex shader functionality.

We present an alternative method for viewing time-varying volumetric data. We consider such data as a four-dimensional data field, rather than considering space and time as separate entities. If we treat the data in this manner, we can apply high dimensional slicing and projection techniques to generate an image hyperplane. The user is provided with an intuitive user interface to specify arbitrary hyperplanes in 4D, which can be displayed with standard volume rendering techniques. From the volume specification, we are able to extract arbitrary hyperslices, combine slices together into a hyperprojection volume, or apply a 4D raycasting method to generate the same results. In combination with appropriate integration operators and transfer functions, we are able to extract and present different space-time features to the user.

One of the most important goals in volume rendering is to be able to visually separate and selectively enable specific objects of interest contained in a single volumetric data set, which can be approached by using explicit segmentation information. We show how segmented data sets can be rendered interactively on current consumer graphics hardware with high image quality and pixel-resolution filtering of object boundaries. In order to enhance object perception, we employ different levels of object distinction. First, each object can be assigned an individual transfer function, multiple of which can be applied in a single rendering pass. Second, different rendering modes such as direct volume rendering, iso-surfacing, and non-photorealistic techniques can be selected for each object. A minimal number of rendering passes is achieved by processing sets of objects that share the same rendering mode in a single pass. Third, local compositing modes such as alpha blending and MIP can be selected for each object in addition to a single global mode, thus enabling high-quality two-level volume rendering on GPUs.

We describe an animated electro-holographic visualization of brain lesions due to the progression of multiple sclerosis. A research case study is used which documents the expression of visible brain lesions in a series of magnetic resonance imaging (MRI) volumes collected over the interval of one year. Some of the salient information resident within this data is described, and the motivation for using a dynamic spatial display to explore its spatial and temporal characteristics is stated. We provide a brief overview of spatial displays in medical imaging applications, and then describe our experimental visualization pipeline, from the processing of MRI datasets, through model construction, computer graphic rendering, and hologram encoding. The utility, strengths and shortcomings of the electro-holographic visualization are described and future improvements are suggested.

Segmentation of the tracheo-bronchial tree of the lungs is notoriously difficult. This is due to the fact that the small size of some of the anatomical structures is subject to partial volume effects. Furthermore, the limited intensity contrast between the participating materials (air, blood, and tissue) increases the segmentation of difficulties. In this paper, we propose a hybrid segmentation method which is based on a pipeline of three segmentation stages to extract the lower airways down to the seventh generation of the bronchi. User interaction is limited to the specification of a seed point inside the easily detectable trachea at the upper end of the lower airways. Similarly, the complementary vascular tree of the lungs can be segmented. Furthermore, we modified our virtual endoscopy system to visualize the vascular and airway system of the lungs along with other features, such as lung tumors.

We introduce a new method for visualizing symmetric tensor fields. The technique produces images and animations reminiscent of line integral convolution (LIC). The technique is also slightly related to hyperstreamlines in that it is used to visualize tensor fields. However, the similarity ends there. HyperLIC uses a multi-pass approach to show the anisotropic properties in a 2D or 3D tensor field. We demonstrate this technique using data sets from computational fluid dynamics as well as diffusion-tensor MRI.

The following topics are dealt with: medical visualization; isosurfaces; implicit surfaces; flow visualization; terrains and view-dependent methods; segmentation and feature analysis; haptics and physical simulation; hardware-assisted volume rendering; volume rendering acceleration; shading and shape perception; volume reconstruction; volumetric techniques; sample-based rendering; mesh simplification; transfer functions; information visualization; scientific and large data visualization; visualization in medicine and biology; and visualization software.

A new method for the synthesis of dense, vector-field aligned textures on curved surfaces is presented, called IBFVS. The method is based on image based flow visualization (IBFV). In IBFV two-dimensional animated textures are produced by defining each frame of a flow animation as a blend between a warped version of the previous image and a number of filtered white noise images. We produce flow aligned texture on arbitrary three-dimensional triangular meshes in the same spirit as the original method: texture is generated directly in image space. We show that IBFVS is efficient and effective. High performance (typically fifty frames or more per second) is achieved by exploiting graphics hardware. Also, IBFVS can easily be implemented and a variety of effects can be achieved. Applications are flow visualization and surface rendering. Specifically, we show how to visualize the wind field on the earth and how to render a dirty bronze bunny.

We present a technique for direct visualization of unsteady flow on surfaces from computational fluid dynamics. The method generates dense representations of time-dependent vector fields with high spatio-temporal correlation using both Lagrangian-Eulerian advection and image based flow visualization as its foundation. While the 3D vector fields are associated with arbitrary triangular surface meshes, the generation and advection of texture properties is confined to image space. Frame rates of up to 20 frames per second are realized by exploiting graphics card hardware. We apply this algorithm to unsteady flow on boundary surfaces of, large, complex meshes from computational fluid dynamics composed of more than 250,000 polygons, dynamic meshes with time-dependent geometry and topology, as well as medical data.

Simulation of rigid body dynamics has been a field of active research for quite some time. However, the presentation of simulation results has received far less attention so far. We present an interactive and intuitive 3D visualization framework for rigid body simulation data. We introduce various glyphs representing vector attributes such as force and velocity as well as angular attributes including angular velocity and torque. We have integrated our visualization method into an application developed at one of the leading companies in automotive engine design and simulation. We apply our principles to visualization of chain and belt driven timing drives in engines.

Deformable isosurfaces, implemented with level-set methods, have demonstrated a great potential in visualization for applications such as segmentation, surface processing, and surface reconstruction. Their usefulness has been limited, however, by their high computational cost and reliance on significant parameter tuning. This paper presents a solution to these challenges by describing graphics processor (GPU) based on algorithms for solving and visualizing level-set solutions at interactive rates. Our efficient GPU-based solution relies on packing the level-set isosurface data into a dynamic, sparse texture format. As the level set moves, this sparse data structure is updated via a novel GPU to CPU message passing scheme. When the level-set solver is integrated with a real-time volume renderer operating on the same packed format, a user can visualize and steer the deformable level-set surface as it evolves. In addition, the resulting isosurface can serve as a region-of-interest specifier for the volume renderer. This paper demonstrates the capabilities of this technology for interactive volume visualization and segmentation.

We describe an interactive visualization and modeling program for the creation of protein structures "from scratch." The input to our program is an amino acid sequence - decoded from a gene - and a sequence of predicted secondary structure types for each amino acid - provided by external structure prediction programs. Our program can be used in the set-up phase of a protein structure prediction process; the structures created with it serve as input for a subsequent global internal energy minimization, or another method of protein structure prediction. Our program supports basic visualization methods for protein structures, interactive manipulation based on inverse kinematics, and visualization guides to aid a user in creating "good" initial structures.