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http://icatb.sourceforge.net/fusion/fusion_startup.php

A MATLAB toolbox which implements the joint Independent Component Analysis (ICA), parallel ICA and CCA with joint ICA methods. It is used to to extract the shared information across modalities like fMRI, EEG, sMRI and SNP data. * Environment: Win32 (MS Windows), Gnome, KDE * Operating System: MacOS, Windows, Linux * Programming Language: MATLAB * Supported Data Format: ANALYZE, NIfTI-1

Proper citation: Fusion ICA Toolbox (RRID:SCR_003494) Copy   

•   Source: SciCrunch Registry

http://synapses.clm.utexas.edu/tools/reconstruct/reconstruct.stm

A Windows (Win32) software application for montaging, aligning, tracing, measuring, and reconstructing objects from serial microscopic section images. The software is designed for microscopy in which section resolution is much less than section thickness, such as transmitted electron microscopy (EM) where the resolution is a few nanometers while the section thickness is many tens of nanometers. Reconstruct can easily handle series with hundreds of very large, high-resolution section images. It facilitates image cropping, scaling and alignment. Multiple images can be placed side-by-side to make a montage of a section from a mosaic of images. The alignment of adjacent sections can be rapidly compared by either blending the two sections or by flickering between them. Sections can be moved while blended. Reconstruct aids in the calibration of image size. Images taken at different magnifications can be combined, calibrated and aligned. Tools for tracing and editing of objects on sections are provided. Objects can be surfaced from the traces and previewed in an OpenGL-based 3D scene window. The 3D scene can be saved as a bitmap or as a VRML file.

Proper citation: Synapse Web Reconstruct (RRID:SCR_002716) Copy   

•   Source: SciCrunch Registry

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

A lightweight framework for setting up dependency-driven processing pipelines. The tool is essentially a configurable shell script (sh/bash), which can be included in other scripts and primarily provides a small number of utility functions for dependency checking and NFS-safe file locking for cluster processing.

Proper citation: Lightweight Data Pipeline (RRID:SCR_014135) Copy   

•   Source: SciCrunch Registry

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

A collection of methods for comparing the performance of different image algorithms. These methods generate quantitative scores that measure divergences to a standard.

Proper citation: SCORE (RRID:SCR_014165) Copy   

•   Source: SciCrunch Registry

http://coins.mrn.org/

A web-based neuroimaging and neuropsychology software suite that offers versatile, automatable data upload/import/entry options, rapid and secure sharing of data among PIs, querying and export all data, real-time reporting, and HIPAA and IRB compliant study-management tools suitable to large institutions as well as smaller scale neuroscience and neuropsychology researchers. COINS manages over over 400 studies, more than 265,000 clinical neuropsychological assessments, and 26,000 MRI, EEG, and MEG scan sessions collected from 18,000 participants at over ten institutions on topics related to the brain and behavior. As neuroimaging research continues to grow, dynamic neuroinformatics systems are necessary to store, retrieve, mine and share the massive amounts of data. The Collaborative Informatics and Neuroimaging Suite (COINS) has been created to facilitate communication and cultivate a data community. This tool suite offers versatile data upload/import/entry options, rapid and secure sharing of data among PIs, querying of data types and assessments, real-time reporting, and study-management tools suitable to large institutions as well as smaller scale researchers. It manages studies and their data at the Mind Research Network, the Nathan Kline Institute, University of Colorado Boulder, the Olin Neuropsychiatry Research Center (at) Hartford Hospital, and others. COINS is dynamic and evolves as the neuroimaging field grows. COINS consists of the following collaboration-centric tools: * Subject and Study Management: MICIS (Medical Imaging Computer Information System) is a centralized PostgreSQL-based web application that implements best practices for participant enrollment and management. Research site administrators can easily create and manage studies, as well as generate reports useful for reporting to funding agencies. * Scan Data Collection: An automated DICOM receiver collects, archives, and imports imaging data into the file system and COINS, requiring no user intervention. The database also offers scan annotation and behavioral data management, radiology review event reports, and scan time billing. * Assessment Data Collection: Clinical data gathered from interviews, questionnaires, and neuropsychological tests are entered into COINS through the web application called Assessment Manager (ASMT). ASMT's intuitive design allows users to start data collection with little or no training. ASMT offers several options for data collection/entry: dual data entry, for paper assessments, the Participant Portal, an online tool that allows subjects to fill out questionnaires, and Tablet entry, an offline data entry tool. * Data Sharing: De-identified neuroimaging datasets with associated clinical-data, cognitive-data, and associated meta-data are available through the COINS Data Exchange tool. The Data Exchange is an interface that allows investigators to request and share data. It also tracks data requests and keeps an inventory of data that has already been shared between users. Once requests for data have been approved, investigators can download the data directly from COINS.

Proper citation: Mind Research Network - COINS (RRID:SCR_000805) Copy   

•   Source: SciCrunch Registry

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

Simulation software that generates pathological ground truth from a healthy ground truth. The software requires an input directory that describes a healthy anatomy (anatomical probabilities, mesh, diffusion tensor image, etc) and then outputs simulation images.

Proper citation: TumorSim (RRID:SCR_002604) Copy   

•   Source: SciCrunch Registry

http://www.physionet.org/

Collection of dissemination and exchange recorded biomedical signals and open-source software for analyzing them. Provides facilities for cooperative analysis of data and evaluation of proposed new algorithm. Providies free electronic access to PhysioBank data and PhysioToolkit software. Offers service and training via on-line tutorials to assist users at entry and more advanced levels. In cooperation with annual Computing in Cardiology conference, PhysioNet hosts series of challenges, in which researchers and students address unsolved problems of clinical or basic scientific interest using data and software provided by PhysioNet. All data included in PhysioBank, and all software included in PhysioToolkit, are carefully reviewed. Researchers are further invited to contribute data and software for review and possible inclusion in PhysioBank and PhysioToolkit. Please review guidelines before submitting material.

Proper citation: PhysioNet (RRID:SCR_007345) Copy   

•   Source: SciCrunch Registry

https://neuron.yale.edu/neuron/

Software for computational neurophysiology. Simulation environment is used for building and using computational models of neurons and networks of neurons. NEURON Users Group can participate in collaborative development of documentation, tutorials, and software.

Proper citation: NEURON (RRID:SCR_017449) Copy   

•   Source: SciCrunch Registry

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

Software containerized environments for reproducible neuroimaging. Part of ReproNim - Center for Reproducible Neuroimaging Computation. DataLad dataset with collection of popular computational tools provided within ready to use containerized environments.

Proper citation: ReproNim/containers (RRID:SCR_018467) Copy   

•   Source: SciCrunch Registry

https://www.bpforms.org

Software toolkit for unambiguously describing molecular structure of DNA, RNA, and proteins, including non-canonical monomeric forms, crosslinks, nicks, and circular topologies. Aims to help epigenomics, transcriptomics, proteomics, systems biology, and synthetic biology researchers share and integrate information about DNA modification, post-transcriptional modification, post-translational modification, expanded genetic codes, and synthetic parts.

Proper citation: BpForms (RRID:SCR_018653) Copy   

•   Source: SciCrunch Registry

https://www.objtables.org

Software toolkit for creating reusable datasets that are both human and machine readable, combining spreadsheets with schemas including classes, their attributes, type of each attribute, and possible relationships between instances of classes.Consists of format for describing schemas for spreadsheets, numerous data types for science, syntax for indicating class and attribute represented by each table and column in workbook, and software for using schemas to rigorously validate, merge, split, compare, and revision datasets. Used for supplementary materials of journal article, as well as for emerging domains which need to quickly build new formats for new types of data and associated software with minimal effort.

Proper citation: ObjTables (RRID:SCR_018652) Copy   

•   Source: SciCrunch Registry

http://datasets.datalad.org/

DataLad data distribution. Super dataset collating DataLad datasets from various sources including OpenNeuro, CRCNS, etc., to provide unified access to over 200TB of neural data.

Proper citation: datasets.datalad.org (RRID:SCR_019089) Copy   

•   Source: SciCrunch Registry

https://brainlife.io/docs/using_ezBIDS/

Web-based BIDS conversion tool to convert neuroimaging data and associated metadata to BIDS standard. Guided standardization of neuroimaging data interoperable with major data archives and platforms.

Proper citation: ezBIDS (RRID:SCR_025563) Copy   

•   Source: SciCrunch Registry

https://github.com/ccipd/MRQy

Software quality assurance and checking tool for quantitative assessment of magnetic resonance imaging and computed tomography data. Used for quality control of MR imaging data.

Proper citation: MRQy (RRID:SCR_025779) Copy   

•   Source: SciCrunch Registry

http://www.farsight-toolkit.org/wiki/FARSIGHT_Toolkit

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23, 2022. A collection of software modules for image data handling, pre-processing, segmentation, inspection, editing, post-processing, and secondary analysis. These modules can be scripted to accomplish a variety of automated image analysis tasks. All of the modules are written in accordance with software practices of the Insight Toolkit Community. Importantly, all modules are accessible through the Python scripting language which allows users to create scripts to accomplish sophisticated associative image analysis tasks over multi-dimensional microscopy image data. This language works on most computing platforms, providing a high degree of platform independence. Another important design principle is the use of standardized XML file formats for data interchange between modules.

Proper citation: Farsight Toolkit (RRID:SCR_001728) Copy   

•   Source: SciCrunch Registry

http://www.nesys.uio.no/Atlas3D/

A multi-platform visualization tool which allows import and visualization of 3-D atlas structures in combination with tomographic and histological image data. The tool allows visualization and analysis of the reconstructed atlas framework, surface modeling and rotation of selected structures, user-defined slicing at any chosen angle, and import of data produced by the user for merging with the atlas framework. Tomographic image data in NIfTI (Neuroimaging Informatics Technology Initiative) file format, VRML and PNG files can be imported and visualized within the atlas framework. XYZ coordinate lists are also supported. Atlases that are available with the tool include mouse brain structures (3-D reconstructed from The Mouse Brain in Stereotaxic Coordinates by Paxinos and Franklin (2001)) and rat brain structures (3-D reconstructed from The Rat Brain in Stereotaxic Coordinates by Paxinos and Watson (2005)). Experimental data can be imported in Atlas3D and warped to atlas space, using manual linear registration, with the possibility to scale, rotate, and position the imported data. This facilitates assignment of location and comparative analysis of signal location in tomographic images.

Proper citation: Atlas3D (RRID:SCR_001808) Copy   

•   Source: SciCrunch Registry

http://www.nb.uw.edu/

Biomedical technology research center that provides state-of-the-art surface analysis expertise, instrumentation, experimental protocols, and data analysis methods to address surface-related biomedical problems. NESAC/BIO develops and applies surface science methodologies that produce a full understanding of the surface composition, structure, spatial distribution, and orientation of biomaterials and adsorbed biomolecules. The NESAC/BIO program identifies areas where surface science must evolve to keep pace with the growth in biochemical knowledge and biomaterial fabrication technology, and develops instrumentation, experimental protocols, and data analysis methods to achieve this evolution. NESAC/BIO provides state-of-the-art surface analysis tools to researchers in the biomedical community. You can gain access to the NESAC/BIO facilities in one of the following ways: * Collaborative: Propose a project to collaborate on with NESAC/BIO. The project should be rewarding for both groups, and the results should reflect the utility of surface analysis for biomedical research * Service: Ask NESAC/BIO to analyze your biomaterial specimens. The spectra obtained from the analyses will be interpreted for you. * Training: Visit the University of Washington to receive training in surface analysis and personally run experiments for your individual research projects. These experiments should have a high probability for yielding useful information and should not involve the development of new ESCA techniques or methodologies.

Proper citation: National ESCA and Surface Analysis Center for Biomedical Problems (RRID:SCR_001430) Copy   

•   Source: SciCrunch Registry

https://www.mristudio.org/

An image processing program running under Windows suitable for such tasks as tensor calculation, color mapping, fiber tracking, and 3D visualization. Most of operations can be done with only a few clicks. This tool evolved from DTI Studio. Tools in the program can be grouped in the following way: * Image Viewer * Diffusion Tensor Calculations * Fiber Tracking and Editing * 3D Visualization * Image File Management * Region of Interesting (ROI) Drawing and Statistics * Image Registration

Proper citation: MRI Studio (RRID:SCR_001398) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/pneuma/

A set of modules that are used to simulate the autoregulation of the cardiovascular and respiratory systems under conditions of changing sleep-wake state and a variety of physiological and pharmacological interventions. It models the dynamic interactions that take place among the various component mechanisms, including those involved in the chemical control of breathing, heart rate, and blood pressure, as well as the effects of changes in the sleep-wake state and arousal from sleep. PNEUMA includes the autonomic control of the cardiovascular system, chemoreflex and state-related control of breath-to-breath ventilation, state-related and chemoreflex control of upper airway potency, as well as respiratory and circulatory mechanics. The model is capable of simulating the cardiorespiratory responses to sleep onset, arousal, continuous positive airway pressure, the administration of inhaled carbon dioxide and oxygen, Valsalva and Mueller maneuvers, and Cheyne-Stokes respiration during sleep. In PNEUMA 3.0, we have extended the existing integrative model of respiratory, cardiovascular, and sleepwake state control, to incorporate a sub-model of glucoseinsulinfatty acid regulation. The extended model is capable of simulating the metabolic control of glucoseinsulin dynamics and its interactions with the autonomic nervous system. The interactions between autonomic and metabolic control include the circadian regulation of epinephrine secretion, epinephrine regulation on dynamic fluctuations in glucose and free fatty acids in plasma, metabolic coupling among tissues and organs mediated by insulin and epinephrine, as well as the effect of insulin on peripheral vascular sympathetic activity. This extended model represents a starting point from which further in silico investigations into the interaction between the autonomic nervous system and the metabolic control system can proceed. Features in PNEUMA 3.0 * Incorporates metabolic component based on prior models of glucose-insulin regulation and free fatty acid (FFA) regulation. * Changes in sympathetic activity from the autonomic portion of PNEUMA produce changes in epinephrine output, which in turn affects the metabolic sub-model. * Inputs from the dietary intake of glucose and external interventions, such as insulin injections, have also been incorporated. * Also incorporated is autonomic feedback from the metabolic component to the rest of PNEUMA: changes in insulin level lead to changes in sympathetic tone. System Requirements: PNEUMA requires Matlab R2007b or higher with the accompanying version of Simulink to be installed on your computer.

Proper citation: PNEUMA (RRID:SCR_001391) Copy   

•   Source: SciCrunch Registry

http://radiology.arizona.edu/CGRI/

Biomedical technology resource center that develops new gamma-ray imaging instruments and techniques that yield substantially improved spatial and temporal resolutions. The Center makes its imagers and expertise available to a wide community of biomedical and clinical researchers through collaborative and service-oriented interactions. The collaborative research applies these new imaging tools to basic research in functional genomics, proteomics, cancer, cardiovascular disease and cognitive neuroscience, and to clinical research in tumor detection and other selected topics. There are five core research projects: * Detector technology research and development * Reconstruction algorithms and system modeling * Data acquisition, signal processing, and system development * Image-quality assessment and system optimization * Techniques for molecular imaging

Proper citation: Center for Gamma Ray Imaging (RRID:SCR_001384) Copy   

•   Source: SciCrunch Registry