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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Population imaging in neuroepidemiology.

M W Vernooij¹, M de Groot², D Bos¹

¹Departments of Radiology and Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.

Handbook of Clinical Neurology

|September 18, 2016

Summary

Population neuroimaging uses advanced brain scans to explore the "black box" between risk factors and neurological diseases. This helps identify disease markers and at-risk individuals.

Keywords:

CT MRI aging dementia epidemiology imaging population quantification stroke

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Basics of Multivariate Analysis in Neuroimaging Data

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Basics of Multivariate Analysis in Neuroimaging Data

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

Area of Science:

Neuroscience
Epidemiology
Medical Imaging

Background:

Traditional neuroepidemiology treats the link between risk factors and neurological outcomes as a "black box."
Advancements in noninvasive neuroimaging allow direct study of brain changes within this pathway.
This opens avenues for understanding disease mechanisms and identifying at-risk populations.

Purpose of the Study:

To discuss the rationale and methods of population neuroimaging.
To explore various imaging modalities and data extraction techniques.
To consider future directions for neuroimaging in large-scale studies.

Main Methods:

Review of neuroimaging techniques applicable to population studies.
Discussion of methods for extracting visual and quantitative data from brain images.
Analysis of the growing need for collaboration and standardization in population neuroimaging.

Main Results:

Population neuroimaging enables direct investigation of brain changes.
It aids in unraveling complex disease pathways and identifying novel biomarkers.
The field is rapidly advancing due to new technologies and collaborative efforts.

Conclusions:

Population neuroimaging is crucial for understanding neurological disease etiology.
Standardization and collaboration are key to the field's continued progress.
Future applications hold significant promise for public health and clinical practice.