Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been developed.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Keying Into Cognition: Temporal Smoothing of Smartphone Typing Behaviors for Passive Assessment of Processing Speed and Executive Function in Individuals With Mood Disorders.

Cognitive computation·2026
Same author

Instantaneous Frequency: A New Functional Biomarker for Dynamic Brain Causal Networks.

AI in neuroscience·2025
Same author

A simple platelet biomarker is associated with symptom severity in major depressive disorder.

Molecular psychiatry·2025
Same author

A comprehensive survey of complex brain network representation.

Meta-radiology·2025
Same author

TGNet: tensor-based graph convolutional networks for multimodal brain network analysis.

BioData mining·2024
Same author

Using a Novel Digital Go/No-Go to Dissociate Intra-subject Temporal Fluctuations in Reaction Time and Accuracy.

medRxiv : the preprint server for health sciences·2024
Same journal

Benchmarking fMRI Denoising Pipelines.

Human brain mapping·2026
Same journal

Modeled Long-Term Effects of Psilocybin on Dynamic Activity and Effective Connectivity of Fronto-Striatal-Thalamic Circuits.

Human brain mapping·2026
Same journal

Intrinsic Functional Architecture Reflects Individual Differences in Passive Working Memory: An Exploratory Resting-State fMRI Study.

Human brain mapping·2026
Same journal

Symptom Overlap and Neurobiological Similarities Between Posttraumatic Stress Disorder and Tinnitus.

Human brain mapping·2026
Same journal

Test-Retest Reliability of Sensorimotor Activity Measured With Spinal Cord fMRI.

Human brain mapping·2026
Same journal

The Human Visual Claustrum Responses to Physical Stimulus Properties and Subjective Content During Movie Viewing.

Human brain mapping·2026
See all related articles

Related Experiment Video

Updated: May 23, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

Angular versus spatial resolution trade-offs for diffusion imaging under time constraints.

Liang Zhan1, Neda Jahanshad, Daniel B Ennis

  • 1Department of Neurology, Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, California.

Human Brain Mapping
|April 24, 2012
PubMed
Summary
This summary is machine-generated.

Higher angular resolution and larger voxels in diffusion MRI improve signal-to-noise and stability. However, larger voxels can bias fractional anisotropy (FA) estimates, a limitation partially overcome by advanced diffusion models.

Keywords:
angular resolutiondiffusion tensor imaginghigh angular resolution diffusion imagingorientation distribution functionreproducibilityspatial resolutiontensor distribution function

More Related Videos

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope
15:10

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

Published on: October 9, 2014

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

Related Experiment Videos

Last Updated: May 23, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope
15:10

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

Published on: October 9, 2014

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

Area of Science:

  • Neuroimaging
  • Biomedical Engineering
  • Radiology

Background:

  • Diffusion-weighted magnetic resonance imaging (DW-MRI) is crucial for assessing brain integrity and connectivity.
  • Optimizing DW-MRI scanning parameters is vital for accurate, stable, and high-signal-to-noise diffusion measures.
  • Understanding trade-offs between spatial and angular resolution is key for parameter optimization.

Purpose of the Study:

  • To investigate the impact of spatial versus angular resolution trade-offs on diffusion MRI measures.
  • To evaluate how these trade-offs affect standard tensor-derived metrics and advanced diffusion models.
  • To assess the stability and signal-to-noise ratio (SNR) of diffusion measures under varying resolutions.

Main Methods:

  • Eight subjects were scanned twice, 2 weeks apart, using three 7-minute DW-MRI protocols with varying voxel sizes (3.0, 2.7, 2.5 mm) and gradient numbers (48, 41, 37).
  • A DTI phantom was scanned with identical protocols and varying b-values.
  • Diffusion measures (FA, MD, ODF) and stability were assessed, alongside an information uncertainty index.

Main Results:

  • Increased angular resolution and larger voxel sizes enhanced SNR and temporal stability for diffusion MRI measures.
  • Larger voxels introduced partial voluming effects, biasing fractional anisotropy (FA) estimation.
  • Advanced diffusion models beyond the standard tensor model partially mitigated FA bias caused by partial voluming.

Conclusions:

  • Scan time constraints necessitate careful optimization of spatial and angular resolution in DW-MRI.
  • Higher angular resolution generally improves data quality, but spatial resolution impacts partial voluming.
  • Beyond-tensor models offer a promising approach to address biases in diffusion measure estimation, particularly FA.