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

Assessment of Diffusion and Perfusion01:17

Assessment of Diffusion and Perfusion

1.9K
Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this...
1.9K

You might also read

Related Articles

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

Sort by
Same author

Single Season Changes in Resting State Network Power and the Connectivity between Regions: Distinguish Head Impact Exposure Level in High School and Youth Football Players.

Proceedings of SPIE--the International Society for Optical Engineering·2019
Same author

Quantifying the Association between White Matter Integrity Changes and Subconcussive Head Impact Exposure from a Single Season of Youth and High School Football using 3D Convolutional Neural Networks.

Proceedings of SPIE--the International Society for Optical Engineering·2019
Same author

Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks.

Deep learning in medical image analysis and multimodal learning for clinical decision support : Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, held in conjunction with MICCAI 2017 Quebec City, QC,...·2019
Same author

Joint Discriminative and Representative Feature Selection for Alzheimer's Disease Diagnosis.

Machine learning in medical imaging. MLMI (Workshop)·2017
Same author

Single- and Multiple-Shell Uniform Sampling Schemes for Diffusion MRI Using Spherical Codes.

IEEE transactions on medical imaging·2017
Same author

Functional Connectivity Network Fusion with Dynamic Thresholding for MCI Diagnosis.

Machine learning in medical imaging. MLMI (Workshop)·2017

Related Experiment Video

Updated: Mar 9, 2026

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography
13:26

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Published on: August 11, 2016

12.8K

Construction of Neonatal Diffusion Atlases via Spatio-Angular Consistency.

Behrouz Saghafi1, Geng Chen2, Feng Shi1

  • 1Department of Radiology and BRIC, University of North Carolina, Chapel Hill, NC, USA.

Patch-Based Techniques in Medical Imaging : Second International Workshop, Patch-Mi 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016 : Proceedings. Patch-Mi (Workshop) (2Nd : 2016 : Athens, Greece)
|January 11, 2017
PubMed
Summary

This study introduces a novel patch-based method for creating diffusion-weighted imaging (DWI) atlases. The new model-free approach enhances structural detail in neonatal brain atlases compared to traditional averaging methods.

More Related Videos

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

29.4K
Author Spotlight: Deciphering Neural Circuit Formation from Two-Photon Microscopy and Single Neuron Imaging
06:18

Author Spotlight: Deciphering Neural Circuit Formation from Two-Photon Microscopy and Single Neuron Imaging

Published on: November 21, 2023

1.4K

Related Experiment Videos

Last Updated: Mar 9, 2026

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography
13:26

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Published on: August 11, 2016

12.8K
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

29.4K
Author Spotlight: Deciphering Neural Circuit Formation from Two-Photon Microscopy and Single Neuron Imaging
06:18

Author Spotlight: Deciphering Neural Circuit Formation from Two-Photon Microscopy and Single Neuron Imaging

Published on: November 21, 2023

1.4K

Area of Science:

  • Neuroimaging
  • Medical Image Analysis
  • Computational Neuroscience

Background:

  • Diffusion-weighted imaging (DWI) atlases are crucial for understanding human brain development.
  • Current atlas construction often relies on simple averaging after image registration, leading to fuzzy results.
  • Existing methods frequently overlook inter-image correlations by processing gradient directions independently.

Purpose of the Study:

  • To propose a novel patch-based, model-free method for constructing diffusion-weighted imaging (DWI) atlases.
  • To improve the structural detail and accuracy of neonatal brain atlases.
  • To address limitations of current atlas construction techniques, particularly image fusion.

Main Methods:

  • A patch-based approach for DWI atlas construction was developed.
  • The method jointly considers diffusion-weighted images from neighboring gradient directions, unlike independent processing.
  • A group regularization framework was employed to ensure consistent spatio-angular atlas reconstruction.

Main Results:

  • The proposed atlas construction method revealed significantly more structural detail than average atlases, particularly in cortical regions.
  • The model-free atlas demonstrated superior performance in neonatal brain data.
  • The newly constructed atlas yielded greater accuracy when applied to image normalization tasks.

Conclusions:

  • The patch-based, model-free DWI atlas construction method offers improved structural detail and accuracy.
  • This approach effectively captures inter-image correlations, overcoming limitations of simple averaging.
  • The developed atlas is a valuable tool for studying neonatal brain development and improving image normalization.