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AMIDE

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Your rating: None Average: 3.8 (11 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.).

MediPy

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Your rating: None Average: 3.2 (5 votes)

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.

XMedCon

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Your rating: None Average: 1.9 (7 votes)

The project stands for Medical Image Conversion. Released under the (L)GPL licence, it comes with the full C-source code of the library, a flexible command-line utility and a neat graphical front-end using the Gtk+ toolkit. The supported formats are: Acr/Nema 2.0, Analyze (SPM), Concorde/µPET, DICOM 3.0, CTI ECAT 6/7, NIfTI-1, InterFile3.3 and PNG or Gif87a/89a.

FrameWork for Software Production Line (FW4SPL)

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Your rating: None Average: 3 (3 votes)

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.

Ruby DICOM

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Your rating: None Average: 1 (1 vote)

UBY DICOM is a cross-platform library for handling DICOM files and network communication in the Ruby language. DICOM is a standard that is widely used throughout the world for saving and transmitting image data used in medicine. The library supports reading, editing and writing files as well as querying, retrieving and sending files.

Dicom3tools

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Your rating: None Average: 3.9 (7 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."

pydicom

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Your rating: None Average: 3 (2 votes)

pydicom is a pure python package for working with DICOM files. It was made for inspecting and modifying DICOM data in an easy "pythonic" way. The modifications can be written again to a new file. As a pure python package, it should run anywhere python runs without any other requirements.

pydicom is not a DICOM server, and is not primarily about viewing images. It is designed to let you manipulate data elements in DICOM files with python code.

Dicom4j

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Your rating: None Average: 1.3 (4 votes)

The purpose of the dicom4j platform is to provide java components related to the Dicom Standard. For those purpose, the platform is based on 4 areas:

  • framework: framework which implements the standards
  • toolkit: offer ways to easily develop software based on the framework
  • plugins: end-user components which adress commons needs you can find in most dicom applications
  • apps: stand alone applications for end-user or tests purpose

DataViewer3D (DV3D)

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Your rating: None Average: 3 (1 vote)

DataViewer3D (DV3D) is a multi-modal imaging data visualization tool offering a cross-platform, open-source solution to simultaneous data overlay visualization requirements of imaging studies.

MITO - Medical Imaging TOolkit

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Your rating: None Average: 4.6 (5 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.

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