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ezDICOM

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Your rating: None Average: 4 (6 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.

Ginkgo CADx

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Your rating: None Average: 3.8 (6 votes)

Ginkgo CADx project started in 2009 with the aim to create an interactive, universal, homogeneous, open-source and cross-platform CADX environment.

Ginkgo is built over a huge amount of advanced technologies providing full abstraction of complex tasks as:

Open Source Picture Archiving and Communication System (OSPACS)

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Your rating: None Average: 3.6 (19 votes)

Open Source Picture Archiving and Communication System (OSPACS) for storing and displaying medical image files. This is currently been used by the Institute of Women's Health (University College London) to archive ultrasound images from the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) and aims to store more than 100,000 DICOM files.

MIView

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Your rating: None Average: 2.1 (7 votes)

MIView is an OpenGL based medical image viewer that contains useful tools such as a DICOM anonymizer and format conversion utility. MIView can read DICOM, Analyze/Nifti, and raster images, and can write Analyze/Nifti and raster images. It can also read and convert DICOM mosaic images. The main goal of MIView is to provide a platform to load any type of medical image and be able to view and manipulate the image. Volume rendering is the main type of advanced visualization that I'm trying to implement.

RT_Image

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Your rating: None Average: 4 (4 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.

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.

OMERO

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Your rating: None Average: 5 (2 votes)

OMERO is client-server software for visualisation, management and analysis of biological microscope images.

From the microscope to publication, OMERO handles all your images in a secure central repository. You can view, organise, analyse and share your data from anywhere you have internet access. Work with your images from a desktop app (Windows, Mac or Linux), from the web or from 3rd party software.

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.).

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.

Insight Segmentation and Registration Toolkit (ITK)

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Your rating: None Average: 3.2 (5 votes)

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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