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convolution superposition  (TomoTherapy)

 
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    Structured Review

    TomoTherapy convolution superposition
    Treatment planning algorithms approved by legacy RTOG for calculation of dose within a medium with heterogeneities
    Convolution Superposition, supplied by TomoTherapy, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/convolution+layer+optimization+program/pmc05551391-38-2-0?v=TomoTherapy
    Average 90 stars, based on 1 article reviews
    convolution superposition - by Bioz Stars, 2026-07
    90/100 stars

    Images

    1) Product Images from "Consensus guidelines for postoperative stereotactic body radiation therapy for spinal metastases: results of an international survey"

    Article Title: Consensus guidelines for postoperative stereotactic body radiation therapy for spinal metastases: results of an international survey

    Journal: Journal of neurosurgery. Spine

    doi: 10.3171/2016.8.SPINE16121

    Treatment planning algorithms approved by legacy RTOG for calculation of dose within a medium with heterogeneities
    Figure Legend Snippet: Treatment planning algorithms approved by legacy RTOG for calculation of dose within a medium with heterogeneities

    Techniques Used:



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    convolution layer optimization program  (Xilinx Inc)
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    Xilinx Inc convolution layer optimization program
    Parameters of a single <t> convolution </t> layer.
    Convolution Layer Optimization Program, supplied by Xilinx Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Image Search Results


    Parameters of a single convolution layer.

    Journal: PLoS ONE

    Article Title: Research on OpenCL optimization for FPGA deep learning application

    doi: 10.1371/journal.pone.0222984

    Figure Lengend Snippet: Parameters of a single convolution layer.

    Article Snippet: Moreover, this paper also tests the performance of the convolution layer optimization program provided by Xilinx, as summarized in where it can be seen that the final performance of the program is 29 times higher than that of the optimization program provided by Xilinx company.

    Techniques:

    The specific code optimization of convolution multiplication calculation.

    Journal: PLoS ONE

    Article Title: Research on OpenCL optimization for FPGA deep learning application

    doi: 10.1371/journal.pone.0222984

    Figure Lengend Snippet: The specific code optimization of convolution multiplication calculation.

    Article Snippet: Moreover, this paper also tests the performance of the convolution layer optimization program provided by Xilinx, as summarized in where it can be seen that the final performance of the program is 29 times higher than that of the optimization program provided by Xilinx company.

    Techniques:

    Performance comparison of the different optimization programs in the convolution layer OpenCL.

    Journal: PLoS ONE

    Article Title: Research on OpenCL optimization for FPGA deep learning application

    doi: 10.1371/journal.pone.0222984

    Figure Lengend Snippet: Performance comparison of the different optimization programs in the convolution layer OpenCL.

    Article Snippet: Moreover, this paper also tests the performance of the convolution layer optimization program provided by Xilinx, as summarized in where it can be seen that the final performance of the program is 29 times higher than that of the optimization program provided by Xilinx company.

    Techniques: Comparison

    Performance comparison of different convolution scale optimization program with Xilinx company.

    Journal: PLoS ONE

    Article Title: Research on OpenCL optimization for FPGA deep learning application

    doi: 10.1371/journal.pone.0222984

    Figure Lengend Snippet: Performance comparison of different convolution scale optimization program with Xilinx company.

    Article Snippet: Moreover, this paper also tests the performance of the convolution layer optimization program provided by Xilinx, as summarized in where it can be seen that the final performance of the program is 29 times higher than that of the optimization program provided by Xilinx company.

    Techniques: Comparison

    Optimized speed-up ratio of different scale convolution.

    Journal: PLoS ONE

    Article Title: Research on OpenCL optimization for FPGA deep learning application

    doi: 10.1371/journal.pone.0222984

    Figure Lengend Snippet: Optimized speed-up ratio of different scale convolution.

    Article Snippet: Moreover, this paper also tests the performance of the convolution layer optimization program provided by Xilinx, as summarized in where it can be seen that the final performance of the program is 29 times higher than that of the optimization program provided by Xilinx company.

    Techniques: