Search Results for "parallel image segmentation"
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Showing 14 open source projects for "parallel image segmentation"
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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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Gimias
Graphical Interface for Medical Image Analysis and Simulation
GIMIAS is a workflow-oriented environment for solving advanced biomedical image computing and individualized simulation problems, which is extensible through the development of problem-specific plug-ins. In addition, GIMIAS provides an open source framework for efficient development of research and clinical software prototypes integrating contributions from the Physiome community while allowing business-friendly technology transfer and commercial product development. -
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BioImageXD - free open source software for analysis, processing and 3D rendering of multi dimensional, multi data channel, time series image data from microscopy and other sources.
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ITK-SNAP x64
ITK-SNAP static builds for Windows 64-bit(only one file)
ITK-SNAP is a software application used to segment structures in 3D medical images. It is the product of a decade-long collaboration between Paul Yushkevich, Ph.D., of the Penn Image Computing and Science Laboratory (PICSL) at the University of Pennsylvania, and Guido Gerig, Ph.D., of the Scientific Computing and Imaging Institute (SCI) at the University of Utah, whose vision was to create a tool that would be dedicated to a specific function, segmentation, and would be easy to use and learn. ITK-SNAP is free, open-source, and multi-platform. -
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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. ... -
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MITO Leap Motion Fork is a fork of the Medical Imaging TOolkit. It integrate the Leap SDK so that you can interact with the application using hand gestures.
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"MITO - Medical Imaging TOolkit" is an open-source, Windows-based software architecture for advanced Medical Imaging. Main characteristics are: DICOM compliant, 2D/3D/S3D visualization, image segmentation and fusion, ROI, advanced 3D user interface
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3D medical image platform for visualization and image processing. Segmentation with Levels sets. Surface reconstruction with marching Cubes, texture Mapping and Raycasting,DICOM support. Integration environment for VTK, ITK and vtkInria3D under wxWidgets
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SMIT (Scientific & Medical Imaging Tool) assists in image analysis of 3D datasets. It supports image registration, image segmentation, 3D ROI analysis, and least square fitting. Its powerful OpenGL engine displays your data fast and accurately. Enjoy!
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Open Source and Portable object oriented software for 3D digital image segmentation and visualization. Pipes and Filters Architechture. Implemented in C++, and uses FLTK, VTK, ITK, TCL (plugins), and pipeline filters implemented in XML. DICOM support.
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OpenVL is a framework for handling, processing & visualizing volumetric data (CT, MRI etc). It provides: powerful data access & layout API, plugins for volume processing tasks (image processing, segmentation etc), and support for multiple file-formats.
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The Volume Browser is a graphical tool to navigate 3D Voxel Data. Additional features are: - Segmentation - Color Coding - 3D and 2D Browsing
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The 3D Slicer is freely available, open-source software for visualization, registration, segmentation, and quantification of medical image data. Follow the link for more info: http://slicer.org
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Monk Computer Vision
A low code unified framework for computer vision and deep learning
... - Monk Object Detection - https://github.com/Tessellate-Imaging/Monk_Object_Detection. Monk object detection is our take on assembling state of the art object detection, image segmentation, pose estimation algorithms at one place, making them low code and easily configurable on any machine. - Monk GUI - https://github.com/Tessellate-Imaging/Monk_Gui. An interface over these low code tools for non coders.
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