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Mayam

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Your rating: None Average: 1.9 (9 votes)

A Cross-platform DICOM viewer developed in Java using the dcm4che toolkit. Mayam is still work under progress. The current features are:

  • DICOM Listener for Q/R
  • DICOM Send
  • Local DB for storing study information
  • Importing DICOM studies from local disk
  • Parsing DicomDir from local disk or CD
  • Query compressed studies without decompressing them
  • Multiple Studies viewer using Layout,Tab view

MITO - Medical Imaging TOolkit

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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.

TutatiX

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Your rating: None Average: 3.5 (2 votes)

TutatiX it's a Dicom Viewer written in python. TutatiX try to be a guide to known how Dicom works and how to develop an application. The must important part of TutatiX it's the documentation that must be detailed and easy to understand.

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.

DICoogle

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Your rating: None Average: 4.1 (21 votes)

Dicoogle PACS is a distributed medical image system and offers the following features:

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: 4.7 (3 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.

ImageJ

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Your rating: None Average: 3.6 (9 votes)

ImageJ is a public domain Java image processing program inspired by NIH Image for the Macintosh. It runs, either as an online applet or as a downloadable application, on any computer with a Java 1.4 or later virtual machine. Downloadable distributions are available for Windows, Mac OS, Mac OS X and Linux.

RT_Image

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Your rating: None Average: 3.7 (3 votes)

RT_Image is an application developed in the Department of Radiation Oncology and MIPS at Stanford University. Coded in the Interactive Data Language (IDL, ITT Visual Information Solutions), RT_Image was originally designed in 2003 to generate radiotherapy target volumes from positron emission tomography (PET) datasets. It has since evolved to embody a variety of tools for visualizing, quantitating, and segmenting three-dimensional images.

AMIDE

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Your rating: None Average: 3.4 (8 votes)

Amide's a Medical Imaging Data Examiner (AMIDE) is a completely free tool for viewing, analysing, and registering volumetric medical imaging data sets. It's been written on top of GTK+ , and runs on any system that supports this toolkit (Linux, Windows, Mac OS X with fink, etc.).

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