Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Rendering volumetric data using STICKS representation scheme
VVS '90 Proceedings of the 1990 workshop on Volume visualization
A multi-threaded streaming pipeline architecture for large structured data sets
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Adaptively sampled distance fields: a general representation of shape for computer graphics
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Alias-Free Voxelization of Geometric Objects
IEEE Transactions on Visualization and Computer Graphics
Large-Scale Data Visualization Using Parallel Data Streaming
IEEE Computer Graphics and Applications
Out-Of-Core Rendering of Large, Unstructured Grids
IEEE Computer Graphics and Applications
Computer
Muliscale Vessel Enhancement Filtering
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
3D Distance Fields: A Survey of Techniques and Applications
IEEE Transactions on Visualization and Computer Graphics
Streaming computation of Delaunay triangulations
ACM SIGGRAPH 2006 Papers
Streaming compression of tetrahedral volume meshes
GI '06 Proceedings of Graphics Interface 2006
Streaming Simplification of Tetrahedral Meshes
IEEE Transactions on Visualization and Computer Graphics
Comparison of Four Freely Available Frameworks for Image Processing and Visualization That Use ITK
IEEE Transactions on Visualization and Computer Graphics
The VRE volume rendering engine
Proceedings of the 26th Spring Conference on Computer Graphics
Streamed watershed transform on GPU for processing of large volume data
Proceedings of the 28th Spring Conference on Computer Graphics
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Although the main memory capacity of modern computers is constantly growing, the developers and users of data manipulation and visualization tools fight all over again with the problem of its shortage. In this paper, we advocate slice-based streaming as a possible solution for the memory shortage problem in the case of preprocessing and analysis of volumetric data defined over Cartesian, regular and other types of structured grids. In our version of streaming, data flows through independent processing units---filters---represented by individual system processes, which store each just a minimal fraction of the whole data set, with a slice as a basic data entity. Such filters can be easily interconnected in complex networks by means of standard interprocess communication using named pipes and are executed concurrently on a parallel system without a requirement of specific modification or explicit parallelization. In our technique, the amount of stored data by a filter is defined by the algorithm implemented therein, and is in most cases as small as one data slice or only several slices. Thus, the upper bound on the processed data volume is not any more defined by the main memory size but is shifted to the disc capacity, which is usually orders of magnitude larger. We propose implementations of this technique for various point, local and even global data processing operations, which may require multiple runs over the input data or eventually temporary data buffering. Further, we give a detailed performance analysis and show how well this approach fits to the current trend of employing cheap multicore processors and multiprocessor computers.