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http://www.nmr.mgh.harvard.edu/CFNT/index

Biomedical technology research center that develops and applies innovative neuroimaging technologies and techniques to enable closer examination of the human brain, and thereby contribute to better understanding of the brain in health and disease. They develop new techniques and advance existing technologies for acquisition and analysis of functionally specific images of the working brain, with unprecedented physiological precision and spatiotemporal resolution. The research and development aims to improve and extend existing methods for non-invasive magnetic resonance image analysis and acquisition, electromagnetic source imaging, optical neuroimaging, and most recently, combined MR-PET neuroimaging. The Resource provides an essential interactive environment, within which an interdisciplinary team of highly skilled scientists, engineers, and clinicians with diverse expertise in multiple modalities and disciplines. The resource supports service use of the Center's facilities by neuroscientists throughout the country, provide extensive training opportunities for students, fellows, and staff scientists, and seek to advance the field of brain mapping through active dissemination of new knowledge and technology.

Proper citation: Center for Functional Neuroimaging Technologies (RRID:SCR_001423) Copy   

•   Source: SciCrunch Registry

http://www.utsouthwestern.edu/education/medical-school/departments/airc/southwestern-nmr-center/index.html

Biomedical technology research center that develops and applies new methods for analysis of metabolic networks in intact tissues, animals and human patients. The importance of understanding abnormal metabolism in common diseases such as cancer, diabetes and heart disease has long been appreciated. Because of constraints in technology, however, much of this research has been conducted in isolated systems where clinical relevance may be uncertain. Progress in magnetic resonance technology provides a foundation for major advances towards new ways of imaging metabolism in patients. These new techniques offer the advantage of imaging biochemical pathways without radiation. The focus of this Resource is to bring these technologies to a level where clinical research is feasible through the development of new MR contrast agents, NMR spectroscopy at high fields, and imaging of hyperpolarized 13C.

Proper citation: Southwestern NMR Center for In Vivo Metabolism (RRID:SCR_001429) Copy   

•   Source: SciCrunch Registry

http://web.mit.edu/fbml/cmr.shtml#

Biomedical technology research center designated as a biotechnology nuclear magnetic resonance (NMR) resource that hosts research efforts into cancer, neurological diseases, and many other areas. The heart of the 900 MHz magnetic resonance instrument is a superconducting magnet with a field strength of 21 Tesla, the highest field currently available for magnetic resonance spectroscopy, roughly 400,000 times stronger than the earth's magnetic field. Magnetic resonance is a powerful tool for determining the structure of molecules, and has proven especially useful for elucidating the role of proteins in biological processes and diseases. The state of the art facility includes two 17.6 T magnets with a third to be delivered in 2000. With multiple 17.6 T NMR magnets, the CMR is a valuable resource in New England and will continue to serve this research community for years to come. The advent of high magnetic fields has placed demands on the hardware needed to run experiments in these very high fields. The CMR has recently produced new advances in NMR probe technology, in electron magnetic resonance, and in using microwaves to enhance NMR experiments. The results are powerful new methods for performing biological research and they are looking forward to the continued growth of these exciting new areas!

Proper citation: MIT/ Harvard Center for Magnetic Resonance (RRID:SCR_001412) Copy   

•   Source: SciCrunch Registry

http://www.nrims.harvard.edu/

Biomedical technology research center with the focus on the application to biomedical research of a new generation of secondary ion mass spectrometer (SIMS), the Multi-Isotope Imaging Mass Spectrometer (MIMS). MIMS is an ion microscope and an ion counter. MIMS provides high mass separation at high transmission (M/lambdaM > 10,000), high spatial resolution (< 40 nm) and has the unique capability of simultaneously recording several atomic mass images. Of the utmost importance, MIMS makes it possible for the first time (and at the intracellular level) to simultaneously image the distribution and measure the accumulation of molecules labeled with any isotopes, in particular with stable isotopes, for example with 15N. Thus, MIMS allows one to study localization, accumulation and turnover of proteins, fats, sugars and foreign molecules in cellular microdomains, donor-receiver cellular trafficking, stem cell nesting and localization of drugs. Their aim is to be a technological, methodological, and intellectual resource for researchers from a variety of disciplines. They seek to explore and develop the unique capabilities of MIMS and to bring cutting-edge information to biology and medicine that is currently unobtainable using existing technologies.

Proper citation: National Resource for Imaging Mass Spectrometry (RRID:SCR_001416) Copy   

•   Source: SciCrunch Registry

http://cng.gmu.edu/brava

A database of digital reconstructions of the human brain arterial arborizations from 61 healthy adult subjects along with extracted morphological measurements. The arterial arborizations include the six major trees stemming from the circle of Willis, namely: the left and right Anterior Cerebral Arteries (ACAs), Middle Cerebral Arteries (MCAs), and Posterior Cerebral Arteries (PCAs).

Proper citation: BraVa (RRID:SCR_001407) Copy   

•   Source: SciCrunch Registry

http://fmri.wfubmc.edu/software/PickAtlas

A software toolbox that provides a method for generating Region of Interest (ROI) masks based on the Talairach Daemon database. The atlases include Brodmann area, Lobar, Hemisphere, Anatomic Label (gyral anatomy), and Tissue type. The atlases have been extended to the vertex in MNI space, and corrected for the precentral gyrus anomaly. Additional atlases (including non-human atlases) can be added without difficulty., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: WFU PickAtlas (RRID:SCR_007378) Copy   

•   Source: SciCrunch Registry

http://loni.usc.edu/Software/CFMBIS

A computer-aided tool for 2-D brain image segmentation using an electrostatic charged fluid model. It allows researchers to perform 2-D image segmentation in brain MR image data. Each interactive visualization element corresponding to the embedded function enables the end user to easily manipulate the image data. The visual environment of this tool provides an easy-to-use means of inspection and interpretation of image data using the LONI jViewbox library. CFMBIS uses the Java Image I/O plug-in architecture to read a wide variety of common medical image file formats.

Proper citation: Charged Fluid Model for Brain Image Segmentation (RRID:SCR_008281) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/MultiPhase-SEG

A segmentation software that employs the implementation of the active contours without edges level set based segmentation model. Its features include: segmentation of three-dimensional brain volumes into two or more regions (for example, regions could be WM, GM, and CSF), visualization of surfaces representing boundaries of different brain regions, and being written in Matlab with the ability to run on any platform with Matlab installed.

Proper citation: MultiPhase-SEG (RRID:SCR_008275) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/DSM

The DualSurfaceMin is a C++ implementation of the fully automatic dual surface minimization (DSM) algorithm for the optimization of deformable surfaces. The method is developed for automatic surface extraction from noisy volumetric images. Its features include: global DSM, DSM-OS, and DSM-IS algorithms for automatic surface extraction from volumetric images using deformable simplex meshes; support for the VRML and OFF formats; output pf both triangulated and simplex meshes; and support for the raw and Analyze 7.5 image formats.

Proper citation: DualSurfaceMin (RRID:SCR_008278) Copy   

•   Source: SciCrunch Registry

http://loni.usc.edu/Software/SVT

Software tool for determining the statistically significant regions of activation in single or multi-subject human brain functional studies. It can be also applied to structural brain data for analyzing developmental, dementia and other changes of anatomy over time. This package was originally developed to work on Sun SPARC and SGI stations using the "C" language compiler provided by Sun/SGI as part of the standard system software.

Proper citation: Sub-Volume Thresholding Analysis (RRID:SCR_008272) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/BrainParser

Software that uses a novel statistical-learning technique to segment brain regions of interest (ROIs) based on a training set of data and generates 3D MRI volumes. The software comes pre-trained on a provided data set but can be retrained to work with your desired regions of interest.

Proper citation: LONI Brain Parser (RRID:SCR_009572) Copy   

•   Source: SciCrunch Registry

https://github.com/ReproNim/reproschema

Software standardized framework for creating, sharing, and reusing cognitive and clinical assessments. Standardized form generation and data collection schema to harmonize results by design across projects. Used for enhancing research reproducibility through standardized survey data collection.

Proper citation: ReproSchema (RRID:SCR_027848) Copy   

•   Source: SciCrunch Registry