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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: Jul 5, 2025

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

Precision Brain Morphometry Using Cluster Scanning.

Maxwell L Elliott¹, Jared A Nielsen², Lindsay C Hanford¹

¹Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.

Medrxiv : the Preprint Server for Health Sciences

|January 18, 2024

Summary

This summary is machine-generated.

Cluster scanning with accelerated MRI significantly reduces measurement error in brain morphometry. This technique enhances precision, improving the ability to detect group differences and disease progression.

Keywords:

ADNI Alzheimer’s disease MRI aging gray-to-white matter signal intensity ratio hippocampus

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Last Updated: Jul 5, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

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3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

Published on: May 12, 2019

Area of Science:

Neuroimaging
Radiology
Biostatistics

Background:

Measurement error in structural MRI limits statistical power for detecting group differences and longitudinal changes in brain morphometry.
Accelerated T1-weighted MRI scans (~1 minute) offer morphometric errors comparable to traditional, longer scans.

Approach:

Explored brain morphometry using cluster scanning in a test-retest study of 40 individuals across age and cognitive groups.
Acquired rapid, accelerated (6x) compressed sensing (CSx6) MRI scans.
Pooled estimates from multiple clustered CSx6 acquisitions to increase measurement precision.

Key Points:

Single CSx6 scans had 12% larger morphometric errors than traditional ADNI scans.
Pooling estimates from four CSx6 scans reduced errors by 34% compared to ADNI, with shorter total acquisition time.
Pooling estimates from eight CSx6 scans further reduced errors by 51% compared to ADNI.

Conclusions:

Cluster scanning with accelerated MRI can significantly improve morphometric precision.
This approach enhances statistical power for detecting group differences and longitudinal changes.
Cluster scanning holds potential for developing more sensitive biomarkers for disease progression.