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Volume Rendering
, 1988
"... A technique for rendering images Of volumes containing mixtures of materials is presented. The shading model allows both the interior of a material and the boundary between materials to be colored. Image projection is performed by simulating the absorption of light along the ray path to the eye. The ..."
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Cited by 433 (2 self)
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A technique for rendering images Of volumes containing mixtures of materials is presented. The shading model allows both the interior of a material and the boundary between materials to be colored. Image projection is performed by simulating the absorption of light along the ray path to the eye. The algorithms used are designed to avoid artifacts caused by aliasing and quantization and can be efficiently implemented on an image computer. Images from a variety of applications are shown.
Topological Considerations in Isosurface Generation
 ACM Transactions on Graphics
, 1994
"... A popular technique for rendition of isosurfaces in sampled data is to consider cells with sample points as corners and approximate the isosurface in each cell by one or more polygons whose vertices are obtained by interpolation of the sample data. That is, each polygon vertex is a point on a cell e ..."
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Cited by 96 (0 self)
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A popular technique for rendition of isosurfaces in sampled data is to consider cells with sample points as corners and approximate the isosurface in each cell by one or more polygons whose vertices are obtained by interpolation of the sample data. That is, each polygon vertex is a point on a cell edge, between two adjacent sample points, where the function is estimated to equal the desired threshold value. The two sample points have values on opposite sides of the threshold, and the interpolated point is called an intersection point. When one cell face has an intersection point ineach of its four edges, then the correct connection among intersection points becomes ambiguous. An incorrect connection can lead to erroneous topology in the rendered surface, and possible discontinuities. We show that disambiguation methods, to be at all accurate, need to consider sample values in the neighborhood outside the cell. This paper studies the problems of disambiguation, reports on some solutions, and presents some statistics on the occurrence of such ambiguities. A natural way to incorporate neighborhood information is through the use of calculated gradients at cell corners. They provide insight into the behavior of a function in wellunderstood ways. We introduce two gradientconsistency heuristics that use calculated gradients at the corners of ambiguous faces, as well as the function values at those corners, to disambiguate at a reasonable computational cost. These methods give the correct topology on several examples that caused problems for other methods we examined.
Efficient Volume Visualization of Large Medical Datasets
"... The size of volumetric datasets used in medical environments is increasing at a rapid pace. Due to excessive precomputation and memory demanding data structures, most current approaches for volume visualization do not meet the requirements of daily clinical routine. In this diploma thesis, an appro ..."
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Cited by 9 (1 self)
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The size of volumetric datasets used in medical environments is increasing at a rapid pace. Due to excessive precomputation and memory demanding data structures, most current approaches for volume visualization do not meet the requirements of daily clinical routine. In this diploma thesis, an approach for interactive highquality rendering of large medical data is presented. It is based on imageorder raycasting with objectorder data traversal, using an optimized cache coherent memory layout. New techniques and parallelization strategies for direct volume rendering of large data on commodity hardware are presented. By using new memory efficient acceleration data structures, highquality direct volume rendering of several hundred megabyte sized datasets at subsecond frame rates on a commodity notebook is achieved.
Visualization of Large Scale Volumetric Datasets
, 2005
"... In this thesis, we address the problem of largescale data visualization from two aspects, dimensionality and resolution. We introduce a novel data structure called Differential TimeHistogram Table (DTHT) for visualization of timevarying (4D) scalar data. The proposed data structure takes advant ..."
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In this thesis, we address the problem of largescale data visualization from two aspects, dimensionality and resolution. We introduce a novel data structure called Differential TimeHistogram Table (DTHT) for visualization of timevarying (4D) scalar data. The proposed data structure takes advantage of the coherence in timevarying datasets and allows efficient updates of data necessary for rendering during data exploration and visualization while guaranteeing that the scalar field visualized is within a given error tolerance of the scalar field sampled. To address the highresolution datasets, we propose a hierarchical data structure and introduce a novel hybrid framework to improve the quality of multiresolution visualization. For more accurate rendering at coarser levels of detail, we reduce aliasing artifacts by approximating data distribution with a Gaussian basis at each level of detail and we reduce blurring by using transparent isosurfaces to capture highfrequency features usually missed in coarse resolution renderings.
unknown title
"... A technique for rendering images Of volumes containing mixtures of materials is presented. The shading model allows both the interior of a material and the boundary between materials to be colored. Image projection is performed by simulating the absorption of light along the ray path to the eye. The ..."
Abstract
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A technique for rendering images Of volumes containing mixtures of materials is presented. The shading model allows both the interior of a material and the boundary between materials to be colored. Image projection is performed by simulating the absorption of light along the ray path to the eye. The algorithms used are designed to avoid artifacts caused by aliasing and quantization and can be efficiently implemented on an image computer. Images from a variety of applications are shown.
unknown title
"... Combining the above, we can formalize the problem as follows. We say that two surfaces A and B are approximate within a, if for every point a on A there exists a point b on B such that b is contained in the cube of side 2.1 centered at a, and vice versa. Isosurface Problem input: A uniform sample F ..."
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Combining the above, we can formalize the problem as follows. We say that two surfaces A and B are approximate within a, if for every point a on A there exists a point b on B such that b is contained in the cube of side 2.1 centered at a, and vice versa. Isosurface Problem input: A uniform sample F of an unknown function lover a sampling interval.1, and threshold t E [0,1]. output: A piecewise polygonal surface S such that, (a) S approximates the geometry of I, i.e., S and I are approximate within a, where I is the surface I(x, y, z) = t. (b) S and I have the same topology, i.e., for every pair of sample points u = (i 1a,ha,k1.1), and v = (i2a,jz.1,k2a), u and v are connected by a path in [0, 1]3 that does not pierce S if and only if u and v are connected by a path in [0, 1]3 that does not pierce I. (c) S is of low complexity, i.e., S consists of O(M) polygons, where M is the number of the (N 1)3 cells of F that intersect I. It is clear that without restrictions on the nature of the unknown function f, the isosurface problem is illposed and possesses no algorithm. To remedy this, we can, for instance, limit the function 1 to be representable exactly by a known interpolant of the given data points. As it happens, the sampling number N is usually rather large, say 100, and the number of sample points is of the order of 106. Consequently, the use of smooth interpolants such as higher order polynomials or polynomial splines is forbiddingly expensive. (Wilhelms et al. (1990a) discuss the use of higher degree interpolants in isosurface construction.) Here, we settle for interpolation by the tensor product linear Bspline, more simply known as trilinear interpolation. The trilinear interpolant T interpolating the values of the function 1 at the vertices of a cube of side a may be expressed as follows: