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Medical Imaging Interaction Toolkit (MITK)

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Your rating: None Average: 5 (11 votes)

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:

    PixelMed Java DICOM Toolkit

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    Your rating: None Average: 3.5 (13 votes)

    PixelMed Java DICOM Toolkit is a stand-alone DICOM toolkit that implements code for reading and creating DICOM data, DICOM network and file support, a database of DICOM objects, support for display of directories, images, reports and spectra, and DICOM object validation.

    The toolkit is a completely new implementation, which does not depend on any other DICOM tools, commercial or free. It does make use of other freely available pure Java tools for compression and XML and database support.

    MITK 3M3

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    Your rating: None Average: 4 (2 votes)

    MITK 3M3 is a free and user-friendly application which ensures effective and efficient work, analysis, and visualization of radiological image data.

    MITK 3M3 gives you access to the latest algorithms and methods from research. The cooperation between the German Cancer Research Center (DKFZ) and mint medical allows for a rapid transfer of leading-edge research topics, including diffusion imaging and automated segmentation techniques. MITK 3M3 will be constantly extended with the addition of new software modules to bring the latest research work to your computer.

    DicomBrowser

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    Your rating: None Average: 4.5 (2 votes)

    DicomBrowser is an application for inspecting and modifying DICOM metadata in many files at once. A single imaging session can produce thousands of DICOM files; DicomBrowser allows users to view and edit a whole session—or even multiple sessions—at once. Users can save the original or modified files to disk, or send them across a network to a DICOM C-STORE service class provider, such as a PACS or an XNAT.

    Dicom3tools

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    Your rating: None Average: 4.3 (3 votes)

    "Command line utilities for creating, modifying, dumping and validating files of DICOM attributes, and conversion of proprietary image formats to DICOM. Can handle older ACR/NEMA format data, and some proprietary versions of that such as SPI."

    Grassroots DICOM (GDCM)

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    Your rating: None Average: 3.9 (8 votes)

    Grassroots DICOM (GDCM) is an implementation of the DICOM standard designed to be open source so that researchers may access clinical data directly. GDCM includes a file format definition and a network communications protocol, both of which should be extended to provide a full set of tools for a researcher or small medical imaging vendor to interface with an existing medical database.

    ClearCanvas

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    Your rating: None Average: 3.6 (37 votes)

    ClearCanvas Workstation is our friendly, integrated RIS Client and DICOM PACS viewer. Because it is built on top of our highly extensible application framework, we expect that it will be appropriate not just for radiologists and clinicians, but also researchers who want to build new, cutting edge tools that can be easily "tried out" in a clinical environment. Like our other creations, ClearCanvas Worksation is free and open source.

    Feature Highlights

    • Very easy to use, intuitive interface
    • Integration with ClearCanvas RIS

    ezDICOM

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    Your rating: None Average: 4.8 (4 votes)

    ezDICOM is a medical viewer for MRI, CT and ultrasound images. It can read images from Analyze, DICOM, GE Genesis, Interfile, Siemens Magnetom, Siemens Somatom and NEMA formats. It also includes tools for converting medical images from proprietary format.

    Insight Segmentation and Registration Toolkit (ITK)

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    Your rating: None Average: 5 (1 vote)

    ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both.

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