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.
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 for instance skull stripping, image registration, subcortical segmentation, cortical surface reconstruction, cortical segmentation, cortical thickness estimation, longitudinal processing, fMRI analysis or tractography.
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.
Reduces significantly the effort required to construct specifically tailored, interactive applications for medical image analysis. MITK allows an easy combination of algorithms developed by ITK with visualizations created by VTK and extends these two toolkits with those features, which are outside the scope of both. It adds support for complex interactions with multiple states as well as undo-capabilities, a very important prerequisite for convenient user interfaces.
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