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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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A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

Database integration of protocol-specific neurological imaging datasets.

Emil E Pacurar¹, Sean K Sethi¹, Charbel Habib²

¹Magnetic Resonance Innovations, Inc., Detroit, MI, USA; The MRI Institute for Biomedical Research, Detroit, MI, USA.

|May 12, 2015

Summary

Magnetic Resonance Innovations (MRI) developed a high-quality neuroimaging database for studying traumatic brain injury, multiple sclerosis, Parkinson's disease, and stroke. This resource aids in biomarker discovery and diagnostic tool development.

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Area of Science:

Neuroimaging
Biomedical Data Science

Background:

Magnetic Resonance Innovations (MR Innovations) has accumulated extensive magnetic resonance imaging (MRI) data over many years.
Data originates from diverse scanning sites, unified by MR Innovations' proprietary neuroimaging protocols ensuring quality and consistency.

Purpose of the Study:

To leverage a comprehensive MRI database for advancing neurological research.
To support the development of diagnostic tools and biomarkers for various neurological conditions.

Main Methods:

Aggregating and standardizing multi-site MRI data using established neuroimaging protocols.
Utilizing specialized software for data analysis and signal processing.

Main Results:

The database has been instrumental in establishing disease biomarkers and validating research findings.
Enabled the development and refinement of signal processing algorithms and diagnostic guidelines, such as for cerebral microbleeds.
Facilitated numerous academic dissertations and fostered public and private research collaborations.

Conclusions:

The curated MRI database is a vital resource for researchers and radiologists.
It significantly contributes to the diagnosis of neurological conditions and encourages further data sharing and collaboration.