Debian Science Cognitive neuroscience packages

AMIDE: (Amide's a Medical Imaging Data Examiner) AMIDE is a tool for viewing and analyzing medical image data sets. It's capabilities include the simultaneous handling of multiple data sets imported from a variety of file formats, image fusion, 3D region of interest drawing and analysis, volume rendering, and rigid body alignments.

This software allows for creating, viewing and manipulating surface reconstructions of the cerebral and cerebellar cortex, viewing volumes and for displaying experimental data on the surfaces and volumes. While Caret is primarily a GUI application with 'caret_command' there is also a versatile command line tool, that allows access to a substantial proportion of Caret's functionality.

Caret can download and use stereotaxic atlases (human, monkey, mouse and rat) from an open online database.

Reference:

 Van Essen, D.C., Dickson, J., Harwell, J., Hanlon, D., Anderson, C.H. and
 Drury, H.A. 2001. An Integrated Software System for Surface-based Analyses of
 Cerebral Cortex. Journal of American Medical Informatics Association, 8(5),
 443-459.

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

The dinifti program converts MRI images stored in DICOM format to NIfTI format. The NIfTI format is thought to be the new standard image format for medical imaging and can be used with for example with FSL, AFNI, SPM, Caret or Freesurfer.

dinifti converts single files, but also supports fully automatic batch conversions of complete dicomdirs. Additionally, converted NIfTI files can be properly named, using image series information from the DICOM files.

This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data.

FSLView is part of FSL.

Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA)

This is a software package for the data processing and evaluation of functional magnetic resonance images. The analysis of fMRI data comprises various aspects including filtering, spatial transformation, statistical evaluation as well as segmentation and visualization. All these aspects are covered by LIPSIA. For the statistical evaluation, a number of well established and peer-reviewed algorithms were implemented in LIPSIA that allow an effcient and user-friendly processing of fMRI data sets. As the amount of data that must be handled is enormous, an important aspect in the development LIPSIA was the efficiency of the software implementation.

LIPSIA operates exclusively on data in the VISTA data format. However, the package contains converters for medical image data in iBruker, ANALYZE and NIfTI format -- converting VISTA images into NIfTI files is also supported.

This project stands for Medical Image Conversion. Released under the (L)GPL, 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 currently supported formats are: Acr/Nema 2.0, Analyze (SPM), DICOM 3.0, InterFile 3.3 and PNG.

The program also allows to read unsupported files without compression, to print pixel values or to extract/reorder specified images. It is possible to retrieve the raw binary/ascii image arrays or to write PNG for desktop applications.

This is the command line tool for batch processing.

This package contains tools to manipulate MINC files.

The Minc file format is a highly flexible medical image file format built on top of the NetCDF generalized data format. The format is simple, self-describing, extensible, portable and N-dimensional, with programming interfaces for both low-level data access and high-level volume manipulation. On top of the libraries is a suite of generic image-file manipulation tools. The format, libraries and tools are designed for use in a medical-imaging research environment: they are simple and powerful and make no attempt to provide a pretty interface to users.

Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images.

This package provides the tools that are shipped with the library (nifti_tool, nifti_stats and nifti1_test).

According to its authors, praat is "doing phonetics by computer". Through its graphical interface, several speech analysis functionalities are available: spectrograms, cochleograms, and pitch and formant extraction. Articulatory synthesis, as well as synthesis from pitch, formant, and intensity are also available. Other features are segmentation, labelling using the phonetic alphabet, and computation of statistics. Praat is configurable and extensible through its own scripting language and has provisions for communicating with other programs.

PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package.

The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features

• High-level powerful scripting language (Python)
• Simple syntax
• Use of hardware-accelerated graphics (OpenGL)
• Integration with Spectrascan PR650 for easy monitor calibration
• Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping
• Simple (or complex) GUIs via wxPython
• Easy interfaces to joysticks, mice, sound cards etc. via PyGame
• Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli

Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun).

While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets.

Using PyNIfTI one can easily read and write NIfTI and ANALYZE images from within Python. The NiftiImage class provides Python-style access to the full header information. Image data is made available via NumPy arrays.

PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments.

It provides

• presentation: both visual and auditory stimuli
• responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped
• sync-pulsing: synchronizing your behavioral task with external acquisition hardware
• flexibility of encoding various experiments due to the use of Python as a description language
• fast execution of critical points due to the calls to linked compiled libraries

This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime)

This package provides PyEPL for supported versions of Python.

Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks.

3D Slicer main application.

This project stands for Medical Image Conversion. Released under the (L)GPL, 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 currently supported formats are: Acr/Nema 2.0, Analyze (SPM), DICOM 3.0, InterFile 3.3 and PNG.

The program also allows to read unsupported files without compression, to print pixel values or to extract/reorder specified images. It is possible to retrieve the raw binary/ascii image arrays or to write PNG for desktop applications.

This is the program version for X based on GTK+. Processes only one file at a time.

This metapackage will install Debian Science packages related to typesetting. You might also be interested in the use::typesetting debtag.

FSL is a comprehensive library of image analysis and statistical tools for FMRI, MRI and DTI brain imaging data.

FSL provides an easy to use GUI.

FSL interoperates well with other brain imaging related software. This includes Caret, FreeSurfer (cortical flattening and modelling).

AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA). In addition to its own format AFNI understands the NIfTI format and is therefore easily usable in combination with FSL and Freesurfer.

This package provides a version of the MNI Average Brain (an average of 305 T1-weighted MRI scans, linearly transformed to Talairach space) specially adapted for use with the MNI Linear Registration Package.

• average_305.mnc - a version of the average MRI that covers the whole brain (unlike the original Talairach atlas), sampled with 1mm cubic voxels
• average_305_mask.mnc - a mask of the brain in average_305.mnc
• average_305_headmask.mnc - another mask, required for nonlinear mode

Remark: Michael Hanke agreed to take over his stuff from mentors http://mentors.debian.net/cgi-bin/sponsor-pkglist?action=details;package=mni-autoreg and http://mentors.debian.net/cgi-bin/sponsor-pkglist?action=details;package=mni-autoreg-model to Debian Med svn and start group maintenance.

MNI Non-parametric Non-uniformity Normalization (N3). This package provides the 'nu_correct' tool for unsupervised correction of radio frequency (RF) field inhomogenities in MR volumes. Two packages are provided:

• mni-n3 - provides 'nu_correct'
• libebtks-dev - MNI support library with numerical types and algorithms

Remark: Michael Hanke agreed to take over his stuff from mentors http://mentors.debian.net/cgi-bin/sponsor-pkglist?action=details;package=mni-n3 to Debian Med svn and start group maintenance.

This package provide a library und GUI for analyzing electrophysiological data. The data handling and storage uses a MySQL-server. The package is written in pure Python.

Provides state-of-the art tools for processing EEG and MEG data.

The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005].

The Vision Egg is a programming library that uses standard, inexpensive computer graphics cards to produce visual stimuli for vision research experiments.

BioImage Suite has extensive capabilities for both neuro/cardiac and abdominal image analysis and state of the art visualization. Many packages are available that are highly extensible, and provide functionality for image visualization and registration, surface editing, cardiac 4D multi-slice editing, diffusion tensor image processing, mouse segmentation and registration, and much more. It can be intergrated with other biomedical image processing software, such as FSL and SPM. This site provides information, downloads, documentation, and other resources for users of the software.

BioImage Suite was developed at Yale University and has been extensively used at different labs at Yale since 2004.

There is a forum at BioImage Suite site for discussion of compiling it from source and packaging issues at http://research.yale.edu/bioimagesuite/forum/index.php?board=12.0

BrainVISA is a software, which embodies an image processing factory. A simple control panel allows the user to trigger some sequences of treatments on series of images. These treatments are performed by calls to command lines provided by different laboratories. These command lines, hence, are the building blocks on which are built the assembly lines of the factory. BrainVISA is distributed with a toolbox of building blocks dedicated to the segmentation of T1-weighted MR images. The product of the main assembly line made up from this toolbox is the following: grey/white classification for Voxel Based Morphometry, Meshes of each hemisphere surface for visualization purpose, Spherical meshes of each hemisphere white matter surface, a graph of the cortical folds, a labeling of the cortical folds according to a nomenclature of the main sulci.