Provides a method for multivariate analysis based on machine learning models for neuroimaging data. PRoNTo is open-source, cross-platform, MATLAB-based and Statistical Parametric Mapping (SPM) compatible, therefore being suitable for both cognitive and clinical neuroscience research. It can also be extended via the addition of new feature selection and extraction approaches, validation procedures or classification/regression models.
Allows the analysis and visualization of structural and functional neuroimaging data from cross-sectional or longitudinal studies. FreeSurfer proposes a suite of tools that provide extensive and automated analysis of key features in the human brain. This includes skull stripping, image registration, subcortical segmentation, cortical surface reconstruction, cortical segmentation, cortical thickness estimation, longitudinal processing, fMRI analysis, tractography, FreeView Visualization GUI, etc... FreeSurfer is freely available, runs on a wide variety of hardware and software platforms, and is open source.
Offers a module that enables the evaluation based on Markov chain Monte Carlo (MCMC) and spatial variational Bayes (SVB) method. BFAST3D is an extension of the SPM software, intending to optimize approaches dealing with Bayesian single-subject functional magnetic resonance imaging (fMRI) data analysis. The application can be used to calculate posterior standard deviations and posterior probability maps (PPMs). This software is compatible only with SPM12.
Provides compositional data analysis tools for multi-modal images. Tetrahydra is a library that was developed for magnetic resonance images with multiple contrast. It allows users to choose data points in a 2D histogram and to display selected brain voxels on a 2D slice. This tool can be used for the calculation of the gradient magnitude image.
Interfaces with existing software for analysis of neuroimaging data and comparative development of algorithms. Nipype is an open-source, community-developed, Python-based software package that consists of three components: (1) interfaces to external tools providing a unified way for setting inputs, executing, and retrieving outputs; (2) a workflow engine for creating analysis pipelines; and (3) plug-ins that execute workflows either locally or in a distributed processing environment.
Facilitates the utilization of the scikit-learn package for neuroimaging. Nilearn is useful for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. It plots brain volumes and employs different heuristics to find cutting coordinates. This tool enables researchers to automatically download reference datasets and atlases.
Aims to facilitate data processing. BRANT is a MATLAB-based toolbox that integrates (i) batch processing pipelines for resting-state functional magnetic resonance imaging (rs-fMRI) data preprocessing, (ii) voxel-wise spontaneous activity analysis, (iii) functional connectivity analysis, (iv) complex network analysis, as well as (v) statistical analysis and results visualization. It was designed using dynamically generated GUIs. Users can generate their own GUIs by adding a few lines of MATLAB code.
Enables easy pattern classification of neuroimaging data and offering a broad assortment of machine learning algorithms and feature selection methods. MANIA provides interfaces to common third party software libraries, especially Matlab pattern classification tools. It is easy to use for non-experts, users are encouraged to study the basics of the different methods especially when using advanced and complex algorithms.
Facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process.
An open-source MATLAB toolbox with user-friendly graphical user interfaces, implementing both dynamic functional and effective connectivity for tracking brain dynamics from functional MRI. We provided two strategies for dynamic analysis: (1) the commonly utilized sliding-window analysis and (2) the flexible least squares based time-varying parameter regression strategy. The toolbox also implements multiple functional measures including seed-to-voxel analysis, region of interest (ROI)-to-ROI analysis, and voxel-to-voxel analysis.
Offers a computational model of the brain’s visual system. PyTorch is based on an unsupervised inference model that can learn representations from complex data. It can be employed to determine and decode cortical responses observed with functional magnetic resonance imaging (fMRI) during naturalistic movie stimuli. This tool also provides a control model to predict cortical responses with supervised information.
Offers functions to display images and surfaces. AMILab contains two-dimensional function plot and histogram scripts. It employs the automatic wrapping of the VTK and wxWidgets to proceed. The tool scripting language features can be extended with manual and automatic wrapping. It can be useful for: sub-images, resizing, arithmetic operations, Gaussian convolutions, mathematical morphology, distance transforms and skeletonization.
Allows users to research and visualize medical images. medInria is a platform for the diffusion of research software in medical imaging created by Inria teams. This platform offers several types of functions such as: (1) management of the database and file importation; (2) 2D or 4D visualization; (3) distribution of images processing; (4) segmentation of images or (5) registration of images; (6) filtering of images.
Hosts heterogeneous tools dedicated to neuroimaging research. BrainVISA aims to help researchers in developing new neuroimaging tools, sharing data and distributing software. It offers a way to define viewers which may use any visualization software. Thanks to its data management functions, the tool can define the data types handled by the software, associate key attributes for indexation, and filename patterns to make the link between the filesystem and the database schema.
Intends to analyze experimental data in time-series. Nitime is built around numerical algorithms, including coherency analysis, which provides analysis for time and spectral domains. It aims to help in manipulation of neuroscientific experiments data, from single-cell recordings to functional magnetic resonance imaging (fMRI). The software also includes objects to represent time-series, auxiliary objects with interface to the numerical machinery and eases common analysis tasks.
Offers a toolbox dedicated to the denoising of functional magnetic resonance imaging (fMRI) data using a wavelet-based hierarchical approach. WaveIDioT provides an application that can be run through a graphic user interface. It can be applied after the preprocessing step and allows users to smooth their data without losing essential spatial details.
Handles neuroimaging information. voxbo provides a set of methods which mainly focuses on the analysis of functional magnetic resonance imaging (fMRI) data and the mapping lesions. This application includes features allowing users to perform 3D display, overlap metrics, as well as utilities for format conversion. Additionally, it can be used with both standard and modified generalized linear models (GLMs).
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