Showing 10 open source projects for "parallel image segmentation"

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  • 1
    Octave Forge

    Octave Forge

    A collection of packages providing extra functionality for GNU Octave

    Octave Forge is a central location for collaborative development of packages for GNU Octave. The Octave Forge packages expand Octave's core functionality by providing field specific features via Octave's package system. See https://octave.sourceforge.io/packages.php for a list of all available packages. GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and...
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    Downloads: 2,958 This Week
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  • 2
    ProStack

    ProStack

    ProStack - a platform for image processing and analysis

    ProStack - a platform for image processing and analysis. It implements various image processing methods as separate modules, that can be joined in a complex image processing scenario by use of a graphical user interface. RPMs are available at https://build.opensuse.org/project/repositories/home:mackoel:compbio
    Downloads: 0 This Week
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  • 3

    libsombrero

    Astronomical object/structure detection from 1D and 2D data sets.

    Sombrero is a fast wavelet image processing and object detection C library for astronomical images. Sombrero is named after the "Mexican Hat" shape of the wavelet masks used in image convolution and is released under the GNU LGPL library.
    Downloads: 0 This Week
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  • 4
    ...(Disclaimer: Processing time depends on compute hardware) Typical processing time for 100mb .las is about 2 seconds. 25mb .laz file process in about the same times. Files are processed in parallel using available CPU cores. Pre-built Windows x64 installer available at https://buymeacoffee.com/nathancrews/e/255641
    Downloads: 7 This Week
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    FreeMat
    Freemat is an interpreted, matrix-oriented development environment for engineering and scientific applications, similar to the commercial package MATLAB. Freemat provides visualization, image manipulation, and plotting as well as parallel programming.
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    Downloads: 149 This Week
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  • 6

    Automatic cell lineage reconstruction

    Automatic segmentation and tracking for 3D time-lapse microscopy

    From Amat et al., Nature Methods, 2014*: "The comprehensive reconstruction of cell lineages in complex multicellular organisms is a central goal of developmental biology. We present an open-source computational framework for segmentation and tracking of cell nuclei with high accuracy and speed. We demonstrate its (1) generality, by reconstructing cell lineages in four-dimensional, terabyte-sized image data of fruit-fly, zebrafish and mouse embryos, acquired with three different types of fluorescence microscopes, (2) scalability, by analyzing advanced stages of development with up to 20,000 cells per time point, at 26,000 cells min-1 on a single computer workstation, and (3) ease of use, by adjusting only two parameters across all data sets and providing visualization and editing tools for efficient data curation. ...
    Downloads: 1 This Week
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  • 7
    Pink is an image processing library developed at ESIEE Engineering for research and teaching purposes. It contains implementations of over 200 algorithms for image segmentation and filtering.
    Downloads: 1 This Week
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  • 8
    EPSILON is a powerful Open Source wavelet image compressor. The project is aimed on parallel and robust image processing.
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    Downloads: 27 This Week
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  • 9
    Fourier is a portable image processing and analysis library written in ANSI C. It implements operations such as color space conversions, noise removal, enhancement, morphology, edge detection, thresholding, segmentation, and visual feature extraction
    Downloads: 3 This Week
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  • 10
    Mseg is a generic region-based multi-scale image segmentation algorithm designed with some optimizations for remote sensing imagery. The algorithm can be used as a low level processing part of an object-oriented image analysis system.
    Downloads: 0 This Week
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