Search Results for "java image segmentation"
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Showing 9 open source projects for "java image segmentation"
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BRL-CAD
Open Source Solid Modeling CAD
BRL-CAD is a powerful cross-platform constructive solid geometry solid modeling system that includes an interactive geometry editor, ray-tracing for rendering & geometric analyses, network distributed framebuffer support, image & signal-processing tools. -
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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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Importer library to import assets from different common 3D file formats such as Collada, Blend, Obj, X, 3DS, LWO, MD5, MD2, MD3, MDL, MS3D and a lot of other formats. The data is stored in an own in-memory data-format, which can be easily processed. www.open3mod.com/ is a 3D model viewer and exporter based on Assimp that is also Open Source.
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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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CsGL is OpenGL for the .Net Framework, providing support for OpenGL 1.1 - 1.4 and numerous extensions.
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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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