Showing 6 open source projects for "parallel desktop"

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  • 1
    The new version of MinimPy (MinimPy2) is available for download at: https://osdn.net/dl/minimpy2/MinimPy2.zip Please send your feedback about this new version to mahmood.saghaei@gmail.com (include MinimPy2 in the subject) ============================================================ MinimPy is a desktop application program for sequential allocation of subjects to treatment groups in clinical trials by using the method of minimization. Comprehensive reference help is available at http://minimpy.sourceforge.net MinimPy has been fully described in the following article: Saghaei, M. and Saghaei, S. (2011) Implementation of an open-source customizable minimization program for allocation of patients to parallel groups in clinical trials. ...
    Downloads: 4 This Week
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  • 2

    Ezys

    Ezys 3D medical image registration program

    Ezys is a non-linear 3D medical image registration program. Ezys fully exploits the parallel computing power of inexpensive commercial graphics processing units (GPU), resulting in a very fast and accurate program capable of running on desktop PCs and even some laptops. On these systems, non-linear image registrations take less than a minute to complete. Ezys implements a diffeomorphic inverse consistent image registration algorithm with a demons-style regularization based on a non-parametric free form deformation model. ...
    Downloads: 0 This Week
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  • 3
    Parallel Spectral Deconvolution is a multithreaded ImageJ plugin for spectral image deblurring.
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    Downloads: 8 This Week
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  • 4
    Parallel Iterative Deconvolution is a multithreaded ImageJ plugin for iterative image deblurring.
    Downloads: 6 This Week
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  • 5
    Parallel HRRT Deconvolution is a multithreaded ImageJ plugin for motion correction of PET brain images.
    Downloads: 0 This Week
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  • 6
    Using the CUDA API this project modifies the AutoDock software to run in parallel on NVIDIA GPUs. Users will be able to download and compile the code and use AutoDock on CUDA capable Graphics Cards. Autodock is located at http://autodock.scripps.edu/
    Downloads: 0 This Week
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