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Image Search Results
Journal: International Journal of Biomedical Imaging
Article Title: High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System
doi: 10.1155/2014/376456
Figure Lengend Snippet: Execution time for Jacobian calculation by conventional and Broyden method on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for mesh size (a) 3736, (b) 7465, and (c) 15031.
Article Snippet: The corresponding
Techniques:
Journal: International Journal of Biomedical Imaging
Article Title: High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System
doi: 10.1155/2014/376456
Figure Lengend Snippet: Breakup of the execution time of various computing blocks of the algorithm on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for mesh size (a) 3736, (b) 7465, and (c) 15031.
Article Snippet: The corresponding
Techniques:
Journal: International Journal of Biomedical Imaging
Article Title: High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System
doi: 10.1155/2014/376456
Figure Lengend Snippet: Execution time for an iteration on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for different mesh sizes.
Article Snippet: The corresponding
Techniques:
Journal: International Journal of Biomedical Imaging
Article Title: High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System
doi: 10.1155/2014/376456
Figure Lengend Snippet: Execution time for Jacobian calculation by conventional and Broyden method on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for mesh size (a) 3736, (b) 7465, and (c) 15031.
Article Snippet: The development of
Techniques:
Journal: International Journal of Biomedical Imaging
Article Title: High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System
doi: 10.1155/2014/376456
Figure Lengend Snippet: Breakup of the execution time of various computing blocks of the algorithm on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for mesh size (a) 3736, (b) 7465, and (c) 15031.
Article Snippet: The development of
Techniques:
Journal: International Journal of Biomedical Imaging
Article Title: High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System
doi: 10.1155/2014/376456
Figure Lengend Snippet: Execution time for an iteration on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for different mesh sizes.
Article Snippet: The development of
Techniques:
Journal: Visual Computing for Industry, Biomedicine and Art
Article Title: Optimizing photoacoustic image reconstruction using cross-platform parallel computation
doi: 10.1186/s42492-018-0002-5
Figure Lengend Snippet: Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from MATLAB, performing condition checks, and allocating memory for input and output data. Device code in GPU is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)
Article Snippet: For example, to reconstruct a 200 × 430 × 200 matrix, it takes half an hour on
Techniques: Blocking Assay