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Medical Imaging Interaction Toolkit (MITK)

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The Medical Imaging Interaction Toolkit (MITK) is a free open-source software system for development of interactive medical image processing software. MITK combines the Insight Toolkit (ITK) and the Visualization Toolkit (VTK) with an application framework. As a toolkit, MITK offers those features that are relevant for the development of interactive medical imaging software covered neither by ITK nor VTK.

Core features of the MITK platform:


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    MediPy is a cross-platform software (Windows, Linux, Mac OS), dedicated to the visualization and processing aspects of medical imaging. It is targeted at both physicians and researchers, being both user-friendly and easy to extend. Physicians will benefit from the pre-programmed tasks (e.g. segmentation, registration, detection of lesions) and the possibility to record new tasks, tailoring the software to each user. The use of standard file formats (Analyze/Nifti, Dicom) allows to load image from many sources, as well as integrate to a PACS.

    FrameWork for Software Production Line (FW4SPL)

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    FW4SPL is a component-oriented architecture with the notion of role-based programming. FW4SPL consists of a set of cross-platform C++ libraries. For now, FW4SPL focuses on the problem of medical images processing and visualization.

    MITO - Medical Imaging TOolkit

    Your rating: None Average: 4.5 (4 votes)

    The "MITO - Medical Imaging TOolkit" project coagulates a number of activities aimed at defining and implementing an open-source, cross-platform software architecture for advanced Medical Imaging. MITO toolkit makes it possible to fetch radiological information and images stored in a PACS according to the standard format DICOM, then provides the final user with basic functionalities such as 2D-3D visualization (VR, SR, MIP), image segmentation and fusion, ROI. Moreover, MITO provides interaction techniques for manipulating 3D medical data in a virtual environment by 2 DOF input devices.


    Your rating: None Average: 3.3 (4 votes)

    Spectroscopic Image Visualization and Computing (SIVIC) is an open-source, standards-based software framework and application suite for processing and visualization of DICOM MR Spectroscopy data. Through the use of DICOM, SIVIC aims to facilitate the application of MRS in medical imaging studies.


    Your rating: None Average: 3.5 (2 votes)

    DeVIDE, or the Delft Visualisation and Image processing Development Environment, is a cross-platform software framework for the rapid prototyping, testing and deployment of visualisation and image processing algorithms. The software was developed within the Visualisation group. DeVIDE's primary (and currently only) front-end is a data-flow boxes-and-lines network editor. In this regard, it is very similar to AVS, OpenDX, Khoros or VISSION. DeVIDE integrates functionality from libraries such as VTK, ITK, GDCM, DCMTK, numpy and matplotlib. It is being very actively developed.


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    Ogles2 is an interactive slice and volume visualization and analysis tool based on Open Inventor / Coin3D. Ogles2 allows for reproducing the workflow of frame based stereotactic neurosurgery. In the long run it strives for being an open source stereotactic planning and analysis system. Ogles2 is NOT APPROVED FOR CLINICAL USE.


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    ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities.

    ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.

    Visualization Toolkit (VTK)

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    The Visualization Toolkit (VTK) is an open-source, freely available software system for 3D computer graphics, image processing, and visualization. It consists of a C++ class library and several interpreted interface layers including Tcl/Tk, Java, and Python. VTK supports a wide variety of visualization algorithms including scalar, vector, tensor, texture, and volumetric methods, as well as advanced modeling techniques such as implicit modeling, polygon reduction, mesh smoothing, cutting, contouring, and Delaunay triangulation.