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

2D NMR: Overview of Homonuclear Correlation Techniques01:16

2D NMR: Overview of Homonuclear Correlation Techniques

562
Homonuclear correlation spectroscopy (COSY) is a powerful technique used in Nuclear Magnetic Resonance (NMR) spectroscopy to study the correlations between nuclei of the same type within a molecule. It provides information about scalar couplings between adjacent nuclei, which helps determine connectivity and structural information. There are several COSY variants, each with its unique strengths and experimental parameters.
COSY90 is the standard two-dimensional (2D) COSY experiment that...
562
Two-Dimensional (2D) NMR: Overview01:12

Two-Dimensional (2D) NMR: Overview

1.4K
The 1D NMR spectrum of large and complex molecules like natural products has complicated splitting patterns and overlapping signals, which can be easily interpreted using 2-dimensional (2D) NMR. Unlike 1D NMR, 2D NMR has two frequency axes that provide the coupling information between the nucleus A and nucleus B in a molecule. The process from which 2D spectra are obtained has four steps.
The first step is the preparation period, during which nucleus A is excited with a radiofrequency pulse....
1.4K

You might also read

Related Articles

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

Sort by
Same author

RT-DETR-FCES: a lightweight ship detection algorithm from remote sensing perspective.

Scientific reports·2026
Same author

Community sport participation and mental wellbeing among women of reproductive age in China: A quantitative study.

African journal of reproductive health·2026
Same author

Linalool targets NR3C2 to inhibit NF-κB-mediated gastric cancer progression.

Cell division·2026
Same author

[(bpy)Cu(CF<sub>3</sub>)<sub>3</sub>]-Mediated Trifluoromethylation of Terminal Alkynes under Mild Conditions.

The Journal of organic chemistry·2026
Same author

TAR syndrome causal gene <i>RBM8A</i> is critical for embryonic bone development and proper Hedgehog signaling.

bioRxiv : the preprint server for biology·2026
Same author

Investigation of Flow Boiling Heat Transfer Performance of Grooved Metal Foam (Ni, Cu) Evaporators.

Micromachines·2026

Related Experiment Video

Updated: Dec 29, 2025

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

978

Acceleration of three-dimensional diffusion magnetic resonance imaging using a kernel low-rank compressed sensing

Chaoyi Zhang1, Tanzil Mahmud Arefin2, Ukash Nakarmi3

  • 1Electrical Engineering, University at Buffalo, State University of New York, Buffalo, NY, United States.

Neuroimage
|February 1, 2020
PubMed
Summary

Kernel low rank compressed sensing (KLR-CS) reconstructs high-resolution diffusion MRI data faster. This machine learning approach significantly reduces scan times for preclinical brain imaging, improving microstructure and connectivity studies.

Keywords:
Compressed sensing (CS)Diffusion MRIFiber orientation distribution (FOD)Kernel principal component analysisMouse brainTractography

More Related Videos

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

23.0K
Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring
17:16

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Published on: December 9, 2010

10.7K

Related Experiment Videos

Last Updated: Dec 29, 2025

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

978
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

23.0K
Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring
17:16

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Published on: December 9, 2010

10.7K

Area of Science:

  • Neuroimaging
  • Biophysics
  • Machine Learning

Background:

  • Diffusion Magnetic Resonance Imaging (dMRI) is crucial for brain microstructure and connectivity analysis.
  • Current dMRI acquisition is limited by lengthy scan times, even with parallel imaging.
  • High-resolution 3D dMRI on preclinical systems remains time-consuming.

Purpose of the Study:

  • To develop a novel method for accelerating high-resolution 3D dMRI acquisition.
  • To utilize machine learning for efficient reconstruction of diffusion weighted images (DWIs).
  • To compare the performance of the proposed method against conventional techniques.

Main Methods:

  • Employed kernel principal component analysis (KPCA) to estimate correlations among DWIs.
  • Utilized these correlations as constraints for reconstructing high-resolution DWIs from under-sampled k-space data (KLR-CS).
  • Retrospectively compared KLR-CS with conventional compressed sensing (CS) using 3D dMRI data from post-mortem mouse brains.

Main Results:

  • The KLR-CS method successfully reconstructed high-resolution DWIs from highly under-sampled data.
  • KLR-CS significantly reduced dMRI scan time.
  • KLR-CS outperformed conventional CS for acceleration factors up to 8 in image quality and fiber orientation resolution.

Conclusions:

  • The KLR-CS method offers a feasible and effective approach to accelerate high-resolution 3D dMRI.
  • This technique has the potential to enhance the investigation of brain microstructure and connectivity.
  • Faster dMRI acquisition can advance preclinical neuroscience research.