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SICLE / Small-deformation Inverse-Consistent Linear-Elastic image Registration
Allows users to estimate the forward and reverse transformation between two images. SICLE is an image registration algorithm that determines the forward and reverse transformation between them while minimizing the inverse consistency error. It acts like that to cut the correspondence between these transformations associated with large inverse consistency errors. The estimated transformations are regularized thanks to a thin-plate spline (TPS) model.
BET / Brain Extraction Tool
Deletes non-brain tissue from an image of the whole head. BET can also estimate the inner and outer skull surfaces, and outer scalp surface, if T1 and T2 input images are of good quality. It is very robust and accurate and has been tested on thousands of data sets from a wide variety of scanners and taken with a wide variety of magnetic resonance sequences. BET uses a deformable model that evolves to fit the brain's surface by the application of a set of locally adaptive model forces. The method is very fast and requires no preregistration or other pre-processing before being applied. BET takes about 5-20 sec to run on a modern desktop computer and is freely available, as a standalone program that can be run from the command line or from a simple GUI, as part of FSL (FMRIB Software Library).
Dipy / Diffusion Imaging in Python
Allows to study diffusion Magnetic Resonance Imaging (MRI) data. Dipy is a program allowing users to share their code and experiments. One of its objectives is to provide transparent implementations for all the different steps of the dMRI analysis with a uniform programming interface. It implements two interfaces for probabilistic Markov fiber tracking: (1) it allows the user to provide the distribution evaluated on a discrete set of possible tracking directions, and (2) it accommodates tracking methods where the fiber orientation distribution function (fODF) cannot be easily computed.
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.
Allows to visualize, process, and integrate with anatomical magnetic resonance imaging (MRI) data, magnetoencephalography (MEG) and electroencephalography (EEG) data. Brainstorm aims to provide a set of tools to the scientific community using MEG/EEG as an experimental technique. User can interact with MEG/EEG recordings including various displays of time series, topographical mapping on 2D or 3D surfaces, generation of animations and series of snapshots of identical viewpoints at sequential time points, the selection of channels and time segments, and the manipulation of clusters of sensors.
Calculates the fractal dimensionality of a 3D structure. calcFD is designed to work with intermediate files from FreeSurfer analysis pipeline, but can also use other volumes. The toolbox includes options to use different masking files and is implemented to use either the box-counting or dilation algorithms and to use either the filled volume or just the surface of the structure. The toolbox can easily be run on all of the participants in a FreeSurfer subject folder, or just on specified subject folders. The Matlab toolbox also includes several functions designed to improve functionality, such as the automatic ‘cropping’ of the volume space to the smallest bounding box necessary to contain the volume, improving computation time drastically. Example files are also provided to aid in using the toolbox for the user‘s needs.
A plugin for bone image analysis in ImageJ. BoneJ provides free, open source tools for trabecular geometry and whole bone shape analysis. It calculates several trabecular, cross-sectional and particulate parameters in a convenient format. Java technology allows BoneJ to run on commodity computers, independent of scanner devices, fully utilising hardware resources. ImageJ’s plugin infrastructure provides a flexible working environment that can be tailored to diverse experimental setups. BoneJ is a working program and a starting point for further development, which will be directed by users’ requests and the emergence of new techniques.
Mango / Multi-image Analysis GUI
Automates regional behavioral analysis of human brain images. Mango provides analysis tools and a user interface to navigate image volumes. The tool is ease to use, multi-platform Java application and extensive region of interest tools. It has the ability to add and update software as a plugin module and offers full access to a suite of image viewing and processing features. The software is able to rapidly determine regionally specific behaviors for researchers’ brain studies.
PANDA / Pipeline for Analyzing braiN Diffusion imAges
A MATLAB toolbox for a comprehensive pipeline processing of dMRI dataset, aiming to facilitate image processing for the across-subject analysis of diffusion metrics and brain network constructions. Of note, the processing pipelines in this toolbox have been completely set up, allowing the end-users of dMRI to process the data immediately. After the user sets the input/output and processing parameters through the friendly graphical user interface (GUI), PANDA fully automates all processing steps for datasets of any number of subjects, and results in data pertaining to many diffusion metrics that are ready for statistical analysis at three levels (Voxel-level, ROI-level, and TBSS-level). Additionally, anatomical brain networks can be automatically generated using either deterministic or probabilistic tractography techniques. Particularly, PANDA can run processing jobs in parallel with multiple cores either in a single computer or within a distributed computing environment using a Sun Grid Engine (SGE) system, thus allowing for maximum usage of the available computing resources.
AMIDE / Amide's a Medical Imaging Data Examiner
Displays and analyzes multimodality volumetric medical images. AMIDE provides the research community with a relatively full-featured, freely available, and open source solution for single and multimodality volumetric medical image analysis. It provides a variety of additional features useful to the molecular imaging researcher, including fully three dimensional ROI drawing and analysis for static and dynamic images, two and three way linked viewing (dual cursor mode), rigid body registration using fiducial markers, filtering and cropping of data sets, movie generation, series viewing, and volume rendering.
NMT / National Institute of Mental Health Macaque Template
Provides a high-resolution in vivo magnetic resonance imaging template of the average macaque brain generated from 31 subjects, as well as a neuroimaging tool for improved data analysis and visualization. From the NMT volume, maps of tissue segmentation and cortical thickness were generated. Surface reconstructions and transformations to previously published digital brain atlases are also provided. An analysis pipeline using the NMT automates and standardizes the time-consuming processes of brain extraction, tissue segmentation, and morphometric feature estimation for anatomical scans of individual subjects. The NMT and associated tools thus provide a common platform for precise single-subject data analysis and for characterizations of neuroimaging results across subjects and studies.
ScAnVP / Scan Analysis and Visualization Processor
Processes and analyzes multimodality neuroimaging data. ScAnVP provides applications for retrieving, visualizing, and group processing of single-volume brain images acquired via nuclear medicine and other radiological techniques. The software also includes computing routines for brain mapping analyses of volumes of interest (VOI’s). It includes several functions, for instance to calculate neurobiological parameters from both functional and anatomical brain images, or to extract and convert brain images from various scanners.
Simpleware ScanIP
Provides a software environment for comprehensively processing 3D image data (MRI, CT, micro-CT, FIB-SEM…). Simpleware ScanIP offers powerful image visualisation, analysis, segmentation, and quantification tools. It includes video recording features and options to export surface models/meshes from segmented data for CAD and 3D printing. Additional modules are available for exporting CAE meshes, integrating image data and CAD, exporting NURBS and calculating effective material properties from scans.
Amira 3D Software for Life Sciences
Allows users to visualize, manipulate, and understand data from imaging modalities such as computed tomography, microscopy or Magnetic resonance imaging (MRI). Amira 3D Software for Life Sciences provides features to import and process 2D and 3D images data, visualization techniques and tools for visual analysis. Users can also create and share presentations. The base product can be customized by adding functional extensions to fit special needs in different application areas.
Provides a Bayesian multiresolution approach for variable selection in an ultra-high dimensional feature space. This algorithm can incorporate multi-level structural information into feature selection, leading to biologically more interpretable results and improved performance. It performs variable selection by applying a threshold to the estimated posterior inclusion probabilities. It also avoids introducing latent indictors and complication in posterior computations.
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