Iterative reconstruction algorithms augmented with regularization can produce high-quality reconstructions from few views and even in the presence of significant noise. In this paper we focus on the particularities as...
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ISBN:
(纸本)9781424439317
Iterative reconstruction algorithms augmented with regularization can produce high-quality reconstructions from few views and even in the presence of significant noise. In this paper we focus on the particularities associated with the GPU acceleration of these. First, we introduce the idea of using exhaustive benchmark tests to determine the optimal settings of various parameters in iterative algorithm, here OS-SIRT, which proofs decisive for obtaining optimal GPU performance. Then we introduce bilateral filtering as a viable and cost-effective means for regularization, and we show that GPU-acceleration reduces its overhead to very moderate levels.
We show that the familiar Cartesian lattice, while convenient for signal processing and representation, is suboptimal when it comes to signal fidelity. We explore various applications of optimal sampling lattices, suc...
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We show that the familiar Cartesian lattice, while convenient for signal processing and representation, is suboptimal when it comes to signal fidelity. We explore various applications of optimal sampling lattices, such as the Hexagonal and Body centered Cartesian (BCC) lattices for 3D Computed Tomographic (CT) Reconstruction, both in terms of the (2D) detector and the (3D) reconstructed object. We find that BCC lattices compare favorably with CC lattices for both CT data acquisition and reconstruction. For example they increase the recovery and detectability of small features, such as small tumors in the brain.
Color design forms a crucial part in visual aesthetics, and it has been shown that a visually aesthetic visualization will be looked at more carefully. An important role plays here the choice of a colormap that is com...
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There has been mounting evidence that the familiar Cartesian lattices, while convenient for signal processing and representation, are sub-optimal when it comes to signal fidelity. More suitable in this respect are opt...
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Three-dimensional computed tomography (CT) is a compute-intensive process, due to the large amounts of source and destination data, and this limits the speed at which a reconstruction can be obtained. There are two ma...
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ISBN:
(纸本)081946628X
Three-dimensional computed tomography (CT) is a compute-intensive process, due to the large amounts of source and destination data, and this limits the speed at which a reconstruction can be obtained. There are two main approaches to cope with this problem: (i) lowering the overall computational complexity via algorithmic means, and/or (ii) running CT on specialized high-performance hardware. Since the latter requires considerable capital investment into rather inflexible hardware, the former option is all one has typically available in a traditional CPU-based computing environment. However, the emergence of programmable commodity graphics hardware (GPUs) has changed this situation in a decisive way. In this paper, we show that GPUs represent a commodity high-performance parallel architecture that resonates very well with the computational structure and operations inherent to CT. Using formal arguments as well as experiments we demonstrate that GPU-based 'brute-force' CT (i.e., CT at regular complexity) can be significantly faster than CPU-based as well as GPU-based CT with optimal complexity, at least for practical data sizes. Therefore, the answer to the title question: "Can GPU-based processing beat complexity optimization for CT?" is "Absolutely!".
Volumetric Subdivision (VS) is a powerful paradigm that enables volumetric sculpting and realistic volume deformations that give rise to the concept of "virtual clay". In VS, volumes are commonly represented...
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Triangular B-splines are powerful and flexible in modeling a broader class of geometric objects defined over arbitrary, non-rectangular domains. Despite their great potential and advantages in theory, practical techni...
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Triangular B-splines are powerful and flexible in modeling a broader class of geometric objects defined over arbitrary, non-rectangular domains. Despite their great potential and advantages in theory, practical techniques and computational tools with triangular B-splines are less-developed. This is mainly because users have to handle a large number of irregularly distributed control points over arbitrary triangulation. In this paper, an automatic and efficient method is proposed to generate visually pleasing, high-quality triangular B-splines of arbitrary topology. The experimental results on several real datasets show that triangular B-splines are powerful and effective in both theory and practice.
With the addition of loop and branch capabilities into the GPU programming set, a more natural and free-flowing volume rendering pipeline execution mode recently emerged. While the execution of the looped fragment pro...
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Traditional volume rendering approaches rely on obtaining values of sampled points in volumetric space, typically on a cartesian grid. Often, this cartesian grid is not the original source of the data. For example, in...
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Radial Basis Functions (RBFs) have become a popular rendering primitive, both in surface and in volume rendering. This paper focuses on volume visualization, giving rise to 3D kernels. RBFs are especially convenient f...
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