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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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DeID - a data sharing tool for neuroimaging studies.

Xuebo Song¹, James Wang¹, Anlin Wang¹

¹School of Computing, Clemson University Clemson, SC, USA.

Frontiers in Neuroscience

|October 7, 2015

Summary

This summary is machine-generated.

Sharing human subject data, like neuroimaging, is crucial for scientific integrity. A new Java program, DeID, simplifies de-identification and data integration for researchers, facilitating secure data sharing.

Keywords:

data anonymization data auditing data sharing de-identification neuroimaging

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Area of Science:

Neuroscience
Data Science
Medical Informatics

Background:

Increasing demand for data sharing to enhance scientific integrity and enable novel research.
Challenges in sharing human subject data, particularly neuroimaging, due to de-identification requirements and data integration complexities.
Need for robust methods to de-identify complex datasets while preserving subject-level data associations.

Purpose of the Study:

To develop and present a software tool, DeID, for de-identifying neuroimaging datasets.
To facilitate the secure sharing of integrated, de-identified human subject data.
To support the advancement of research through accessible and shareable data.

Main Methods:

Development of a Java-based program (DeID) with user interaction wizards for data de-identification.
Implementation of functions for auditing and validating de-identified data.
Packaging of de-identified data into a single compressed file for transfer via protocols like FTPS and SFTP.

Main Results:

DeID successfully removes identifying information from neuroimaging datasets.
The software maintains associations between different data types from the same subject.
DeID supports cross-platform compatibility (Windows, Linux, Mac) and an open architecture for adaptability.

Conclusions:

DeID streamlines the complex process of de-identifying and sharing human subject neuroimaging data.
The software promotes scientific integrity and collaborative research by enabling data accessibility.
DeID's design facilitates adaptation for broader data types, aiming to significantly improve data sharing practices.