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http://slicer.org/

A free, open source software package for visualization and image analysis including registration, segmentation, and quantification of medical image data. Slicer provides a graphical user interface to a powerful set of tools so they can be used by end-user clinicians and researchers alike. 3D Slicer is natively designed to be available on multiple platforms, including Windows, Linux and Mac Os X. Slicer is based on VTK (http://public.kitware.com/vtk) and has a modular architecture for easy addition of new functionality. It uses an XML-based file format called MRML - Medical Reality Markup Language which can be used as an interchange format among medical imaging applications. Slicer is primarily written in C++ and Tcl.

Proper citation: 3D Slicer (RRID:SCR_005619) Copy   

•   Source: SciCrunch Registry

http://www.birncommunity.org/tools-catalog/human-imaging-database-hid/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented October 5, 2017.

Database management system developed to handle the increasingly large and diverse datasets collected as part of the MBIRN and FBIRN collaboratories and throughout clinical imaging communities at large. The HID can be extended to contain relevant information concerning experimental subjects, assessments of subjects, the experimental data collected, the experimental protocols, and other metadata normally included with experiments.

Proper citation: Human Imaging Database (RRID:SCR_006126) Copy   

•   Source: SciCrunch Registry

http://bishopw.loni.ucla.edu/AIR5/

A tool for automated registration of 3D (and 2D) images within and across subjects and within and sometimes across imaging modalities. The AIR library can easily incorporate automated image registration into site specific programs adapted to your particular needs.

Proper citation: Automated Image Registration (RRID:SCR_005944) Copy   

•   Source: SciCrunch Registry

http://cibsr.stanford.edu/tools/

A multiplatform, highly modular image processing and visualization application which is under development by the Center for Interdisciplinary Brain Sciences Research. The goal of this project is provide a framework application for neuroimaging which facilitates the interchange of software tools developed by researchers. BrainImageJava can: * Delineate ROIs in slices along X, Y, or Z axes, with 3D feedback in the other axes. * Create and display triangular mesh surfaces from MRI volumes. * Draw Surfaces-of-Interest (SOIs) in 3D, and edit them in a planar display. * Set Talairach grid on a volume, export an AC/PC stack, and measure the values within each grid unit. This 3D image processing and analysis program for the Apple Macintosh PowerPC is based on the public domain application, NIH Image. It includes interactive procedures for 3D MRI quantification including semi-automated procedures for removing non-brain tissues from images, fuzzy segmentation of tissue compartments, global or local parcellation (based on the Talairach atlas), region-growing, etc. The last version of the software included multiplatform capability, volume visualization and advanced image analysis tools.

Proper citation: BrainImage Software (RRID:SCR_006139) Copy   

•   Source: SciCrunch Registry

http://neuro.imm.dtu.dk/software/brede/

A package for neuroinformatics and neuroimaging analysis mostly programmed in Matlab with a few additional programs in Python and Perl. It allows coordinate-based meta-analysis and visualization, neuroimaging analysis of voxel or regional data - not the original data but rather the summary images (e.g., statistical parametric images) and location data in stereotactic space. Among the algorithms implemented are kernel density estimation (for coordinate-based meta-analysis), independent component analysis, non-negative matrix factorization, k-means clustering, singular value decomposition, partial correlation analysis with permutation testing and partial canonical correlation analysis. Visualization of coordinate, surfaces and volumes are possible in 2D and 3D. Generation of HTML for results are possible and algorithms can be accessed from the command line or via a flexible graphical interface. With the Brede Toolbox comes the Brede Database with a small coordinate database from published neuroimaging studies, and ontologies for, e.g., brain function and brain regions.

Proper citation: Brede Toolbox (RRID:SCR_006204) Copy   

•   Source: SciCrunch Registry

http://freesurfer.net/fswiki/HippocampalSubfieldSegmentation

A software package for automatic segmentation of hippocampal subfields in magnetic resonance imges. Given a pair of T1-weighted and T2-weighted images (the latter acquired using a protocol tuned for hippocampus imaging), ASHS will automatically label main subfields of the hippocampus, and some extra-hippocampal structures, using multi-atlas segmentation. The main method is described in the Yushkevich et al. 2011 Neuroimage paper (http://tinyurl.com/cffrp3p). * execution requires: Advanced Normalization Tools, FSL

Proper citation: Segmentation of Hippocampus Subfields (RRID:SCR_005996) Copy   

•   Source: SciCrunch Registry

http://web.mit.edu/swg/software.htm

Toolbox for post-processing fMRI data. Includes software for comprehensive analysis of sources of artifacts in timeseries data including spiking and motion. Most compatible with SPM processing, but adaptable for FSL as well. * Operating System: MacOS, Windows, Linux * Programming Language: MATLAB * Supported Data Format: ANALYZE

Proper citation: Artifact Detection Tools (RRID:SCR_005994) Copy   

•   Source: SciCrunch Registry

http://www.brain-map.org/api/index.html

API and demo application for accessing the Allen Brain Atlas Mouse Brain data. Data available via the API includes download high resolution images, expression data from a 3D volume, 3D coordinates of the Allen Reference Atlas, and searching genes with similar gene expression profiles using NeuroBlast. Data made available includes: * High resolution images for gene expression, connectivity, and histology experiments, as well as annotated atlas images * 3-D expression summaries registered to a reference space for the Mouse Brain and Developing Mouse Brain * Primary microarray results for the Human Brain and Non-Human Primate * RNA sequencing results for the Developing Human Brain * MRI and DTI files for Human Brain The API consists of the following resources: * RESTful model access * Image download service * 3-D expression summary download service * Differential expression search services * NeuroBlast correlative searches * Image-to-image synchronization service * Structure graph download service

Proper citation: Allen Brain Atlas API (RRID:SCR_005984) Copy   

•   Source: SciCrunch Registry

http://connectomes.utah.edu/

A web-compliant application that allows connectomics visualization by converting datasets to web-optimized tiles, delivering volume transforms to client devices, and providing groups of users with connectome annotation tools and data simultaneously via conventional internet connections. Viking is an extensible tool for connectomics analysis and is generalizable to histomics applications.

Proper citation: Viking Viewer for Connectomics (RRID:SCR_005986) Copy   

•   Source: SciCrunch Registry

http://www.unc.edu/~grwu/Software.html

A software plugin for 3D Slicer that matches morphological signatures of medical images automatically. HAMMER is an acronym for Hierarchical Attribute Matching Mechanism for Elastic Registration (Dinggang Shen, Christos Davatzikos, HAMMER: Hierarchical Attribute Matching Mechanism for Elastic Registration, IEEE Trans. on Medical Imaging, 21(11):1421-1439, Nov 2002) - an elastic registration algorithm for medical images, matching morphological signatures of images in a hierarchical multi-scale regime. White matter lesion (WML) segmentation is a novel multi-spectral WML segmentation protocol via incorporating information from T1-w, T2-w, PD-w and FLAIR MR brain images. (Zhiqiang Lao, Dinggang Shen, Dengfeng Liu, Abbas F Jawad, Elias R Melhem, Lenore J Launer, Nick R Bryan, Christos Davatzikos, Computer-Assisted Segmentation of White Matter Lesions in 3D MR images, Using Pattern Recognition, Academic Radiology, 15(3):300-313, March 2008).

Proper citation: Hammer And WML Modules for 3D Slicer (RRID:SCR_005980) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/abc

A comprehensive processing pipeline developed and used at University of North Carolina and University of Utah for brain MRIs. The processing pipeline includes image registration, filtering, segmentation and inhomogeneity correction. The tool is cross-platform and can be run within 3D Slicer or as a stand-alone program. The image segmentation algorithm is based on the EMS software developed by Koen van Leemput.

Proper citation: ABC (Atlas Based Classification) (RRID:SCR_005981) Copy   

•   Source: SciCrunch Registry

http://brainvis.wustl.edu/wiki/index.php/Caret:About

Software package to visualize and analyze structural and functional characteristics of cerebral and cerebellar cortex in humans, nonhuman primates, and rodents. Runs on Apple (Mac OSX), Linux, and Microsoft Windows operating systems.

Proper citation: Computerized Anatomical Reconstruction and Editing Toolkit (RRID:SCR_006260) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/stark_aging/

Behavioral and imaging data from about 120 participants aged 18-89. Data were collected as part of a grant to use high-resolution imaging and advanced behavioral tasks to understand how aging affects the hippocampus and how this is related to age-related cognitive decline. The full dataset includes traditional neuropsycholgical measures, hippocampal-specific behavioral measures, whole-brain DTI, high-resolution DTI of the medial temporal lobes, and structural MRI including segmentation of grey/white/CSF, of cortical regions and of hippocampal subfields.

Proper citation: Stark Cross-Sectional Aging (RRID:SCR_014171) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/ymdti/

A dataset which contains diffusion tensor images of 93 healthy, young male subjects.

Proper citation: YMDTI: Diffusion Tensor Images of Healthy Young Males (RRID:SCR_014183) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/hfh_t1_hp_seg1/

Shared dataset which consists of skull-stripped T1 MRI images and segmented hippocampi of 163 Temporal Lobe Epilepsy (TLE) patients. The T1 and hippocampal segmentation data of TLE patients are uploaded in three separate datasets which can be accessed from the main site.

Proper citation: Epilepsy T1 and Hippocampal Segmentation Datasets (RRID:SCR_014926) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/retro/cobre.html

Data set of raw anatomical and functional MR data from 72 patients with Schizophrenia and 75 healthy controls (ages ranging from 18 to 65 in each group). All subjects were screened and excluded if they had: history of neurological disorder, history of mental retardation, history of severe head trauma with more than 5 minutes loss of consciousness, history of substance abuse or dependence within the last 12 months. Diagnostic information was collected using the Structured Clinical Interview used for DSM Disorders (SCID). A multi-echo MPRAGE (MEMPR) sequence was used with the following parameters: TR/TE/TI = 2530/(1.64, 3.5, 5.36, 7.22, 9.08)/900 ms, flip angle = 7��, FOV = 256x256 mm, Slab thickness = 176 mm, Matrix = 256x256x176, Voxel size =1x1x1 mm, Number of echos = 5, Pixel bandwidth =650 Hz, Total scan time = 6 min. With 5 echoes, the TR, TI and time to encode partitions for the MEMPR are similar to that of a conventional MPRAGE, resulting in similar GM/WM/CSF contrast. Rest data was collected with single-shot full k-space echo-planar imaging (EPI) with ramp sampling correction using the intercomissural line (AC-PC) as a reference (TR: 2 s, TE: 29 ms, matrix size: 64x64, 32 slices, voxel size: 3x3x4 mm3). Slice Acquisition Order: Rest scan - collected in the Axial plane - series ascending - multi slice mode - interleaved MPRAGE - collected in the Sag plane - series interleaved - multi slice mode - single shot The following data are released for every participant: * Resting fMRI * Anatomical MRI * Phenotypic data for every participant including: gender, age, handedness and diagnostic information.

Proper citation: COBRE (RRID:SCR_010482) Copy   

•   Source: SciCrunch Registry

http://www.incf.org/

Independent international facilitator catalyzing and coordinating global development of neuroinformatics aiming to advance data reuse and reproducibility in global brain research. Integrates and analyzes diverse data across scales, techniques, and species to understand brain function and positively impact the health and well being of society.

Proper citation: International Neuroinformatics Coordinating Facility (RRID:SCR_002282) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/cleanline/

An EEGLAB plugin which adaptively estimates and removes sinusoidal artifacts from independent component analysis (ICA) components or scalp channels using a frequency-domain (multi-taper) regression technique with a Thompson F-statistic for identifying significant sinusoidal artifacts. This approach has been advocated by Partha Mitra and Hemant Bokil (Observed Brain Dynamics, Chapter 7.3.4., 2007) and CleanLine utilizes modified routines from the Mitra Lab's Chronux Toolbox (www.chronux.org). Sinusoidal noise can be a prominent artifact in recorded electrophysiological data. This can stem from AC power line fluctuations (e.g. 50/60 Hz line noise + harmonics), power suppliers (e.g. in medical equipment), fluorescent lights, etc. Notch filtering is generally undesirable due to creation of band-holes, and significant distortion of frequencies around the notch frequency (as well as phase distortion at other frequencies and Gibbs rippling in the time-domain).

Proper citation: CleanLine (RRID:SCR_002233) Copy   

•   Source: SciCrunch Registry

http://www.pstnet.com/hardware.cfm?ID=92

MRI Simulator that provides a realistic approximation of an actual MRI scanner to allow habituation and training of participants in an environment less daunting than a real scanner. Special populations such as children, the elderly, and psychiatric patients, are often prone to claustrophobia and anxiety in the bore of a magnet, and consequently have a much higher rate of terminating the experiment or scan session before its completion. Some centers that have dealt with these populations estimate a 50%-80% failure rate. With the use of the MRI Simulator this failure rate can often be reduced below 5%, improving cost effectiveness.

Proper citation: PST MRI Simulator (RRID:SCR_002460) Copy   

•   Source: SciCrunch Registry

http://www.brain.org.au/software/

A collection of tools that generate numerical fiber structures with the complexity of human white matter and simulate Diffusion-Weighted MR images that would arise from them. Its primary use is to enable the testing of tracking algorithms

Proper citation: Numerical Fibre Generator (RRID:SCR_002457) Copy   

•   Source: SciCrunch Registry