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The R Project for Statistical Computing

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Your rating: None Average: 2.7 (3 votes)

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R."

Brainstorm

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Your rating: None Average: 1 (18 votes)

Brainstorm is a collaborative open-source Matlab application dedicated to magnetoencephalography (MEG) and electroencephalography(EEG) data visualization, processing and cortical source estimation.
The intention is to make a comprehensive set of tools available to the scientific community involved in MEG/EEG experimental research.
For physicians and researchers, the interest of this software package resides in its rich and intuitive graphic interface, which does not require any programming knowledge.

PyEPL

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Your rating: None Average: 2.6 (7 votes)

PyEPL (the Python Experiment-Programming Library) is a library for coding psychology experiments in Python. It supports presentation of both visual and auditory stimuli, and supports both manual (keyboard/joystick) and sound (microphone) input as responses.

MeVisLab

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Your rating: None Average: 4.5 (4 votes)

MeVisLab represents a platform for image processing research and development with a focus on medical imaging. It allows fast integration and testing of new algorithms and the development of application prototypes that can be used in clinical environments.

Visualization Toolkit (VTK)

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Your rating: None Average: 2.3 (6 votes)

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.