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.
Computes high-dimensional mappings to capture the statistics of brain structure and function. ANTs allows users to organize, visualize and statistically explore large biomedical image sets. It integrates imaging modalities and related information in space and time, and works across species or organ systems with minimal customization. ANTs depends on the Insight ToolKit (ITK), a widely used medical image processing library to which ANTs developers contribute. ANTs can be used paired with ANTsR, an emerging tool supporting standardized multimodality image analysis. ANTs is popularly considered a state-of-the-art medical image registration and segmentation toolkit.
Provides a set of python scripts for deriving a whole brain parcellation of functional magnetic resonance imaging (fMRI) data. The resulting regions are suitable for use as regions of interest (ROIs) in fMRI data analysis. The pyClusterROI method employs a spatially-constrained normalized-cut spectral clustering algorithm to generate individual-level and group-level parcellations. The spatial constraint is imposed to ensure that the resulting ROIs are spatially coherent, i.e. the voxels in the resulting ROIs are connected. Using this package, clustering can be performed based on either the temporal correlation between voxel time courses, the spatial correlation between whole brain functional connectivity maps generated from each voxel time course, or a by spatial distance.
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.
Extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM) software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF), hippocampus and amygdala. It is able to segment neonatal brain tissues well, even in images that have brain abnormalities common in preterm infants.
Determines lesions in a given anatomical image. ALI is a method build around the SPM software, compatible with SPM5, 8 and 12, which is based on the merging of clustering outlier detection procedure combined with an improvement of the unified segmentation-normalization algorithm. This application can be used on single T1-weighted images for an automatic highlighting of brain tumors.
Permits to analyze functional magnetic resonance imaging (fMRI) data. HeteroscedasticfMRI is based on a Markov Chain Monte Carlo (MCMC) algorithm. It allows for Bayesian variable selection among the regressors to model both the mean and variance. The tool can be used for estimating functional connectivity; for example by using a seed time series as a covariate in the design matrix. The general linear model with autoregressive noise and heteroscedastic noise innovations tends to detect more brain activity, compared to its homoscedastic counterpart.
Derives functional parcellations of the cerebral cortex within individual subjects. MS-HBM takes into account inter-subject and intra-subject functional connectivity variability. It was applied to three multi-session resting-state fMRI datasets from the Genomic Superstruct Project, Hangzhou Normal University of the Consortium for Reliability and Reproducibility, and the Human Connectome Project.
Manages task-based and resting-state functional magnetic resonance imaging (fMRI) for analysis. FMRIPrep is divided into anatomical and functional preprocessing tasks which are both composed of modules that can be merged differently according to the user input data. It encompasses several features such as voxel-based, resting-state connectivity or surface-based analysis. The software can also be run through the OpenNeuro platform or the Singularity container.
Offers a digital imaging and communications in medicine (DICOM) solution. OsiriX is an image processing software that provides displaying, reviewing, interpreting and post-processing image files. It supports DICOM standard for a complete integration in a workflow environment and in a picture archiving and communication system (PACS).
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.
Enables group inferences from functional magnetic resonance imaging (fMRI) data using Independent Component Analysis (ICA). GIFT implements several algorithms allowing independent component analysis and blind source separation of group (and single subject) functional magnetic resonance imaging data. The software can be used for running both single subject and single session analysis as well as group analysis.
Produces a threshold for cluster false discovery rates (FDR). At4fmri is a module, extending the SPM software, intending to assist users in confronting noise and activation to define a fitted threshold. It can also threshold functional magnetic resonance imaging (fMRI) maps as well as write them. The application can be run only through SPM8.
Serves for the creation and visualization of surface reconstructions of the cerebral and cerebellar cortex. Caret provides several features such as viewing and manipulation of experimental data on surfaces and volumes. It has a graphical and interactive interface but provides also a command line option containing up to 200 command-line operations that permits batch processing of neuroimaging data.
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