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Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

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Related Experiment Video

Updated: Apr 28, 2026

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo

Published on: May 4, 2018

A simple tool for neuroimaging data sharing.

Christian Haselgrove¹, Jean-Baptiste Poline¹, David N Kennedy¹

¹University of Massachusetts Medical School Worcester, MA, USA.

Frontiers in Neuroinformatics

|June 7, 2014

Summary

This summary is machine-generated.

Sharing neuroimaging data is challenging due to various barriers. This system simplifies data anonymization and public sharing, making neuroimaging data more accessible for research.

Keywords:

data archiving data processing neuroimaging neuroinformatics quality assessment

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Published on: March 21, 2019

Area of Science:

Neuroscience
Medical Informatics
Data Science

Background:

Despite increasing calls for data sharing in neuroimaging, significant political, financial, social, and technical barriers persist.
Researchers, especially those outside large consortia, lack accessible technical solutions for data sharing.
Time commitment and social factors also hinder the public availability of valuable neuroimaging datasets.

Purpose of the Study:

To present a user-friendly system for sharing neuroimaging data.
To simplify the process of anonymizing and uploading Digital Imaging and Communications in Medicine (DICOM) data.
To provide immediate benefit to data providers through automated quality control.

Main Methods:

Development of a system with a server at the International Neuroinformatics Coordinating Facility (INCF) and user tools.
User tools facilitate easy identification of DICOM data directories, authentication, and session/subject identification.
Automated data anonymization, secure upload to the INCF server, and execution of quality control routines.

Main Results:

The system successfully anonymizes DICOM data and uploads it to the INCF server.
Automated quality control reports are generated alongside the shared data.
Data becomes publicly available with initial quality assessment within minutes of user interaction.
Users retain control over their data and can adjust sharing policies as needed.

Conclusions:

The developed system effectively addresses technical and social barriers to neuroimaging data sharing.
It provides a simple, efficient method for researchers to make their data publicly available.
The system promotes greater accessibility and utilization of neuroimaging data in research.