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

You might also read

Related Articles

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

Sort by
Same author

Time-independent theoretical framework for stroboscopic nonlinear dynamics based on time-nonlocal response.

Optics express·2026
Same author

Inhalable bacteriophage endolysins: a novel therapeutic strategy for drug-resistant bacterial pulmonary infections - a comprehensive review.

Annals of medicine·2026
Same author

Quantitative Assessment of Brain Glucose Metabolism Using Dynamic Glucose-Enhanced Magnetic Resonance Fingerprinting (DGE-MRF).

Chemical & biomedical imaging·2026
Same author

A multi-modal foundation model for brain disease diagnosis and medical imaging.

Patterns (New York, N.Y.)·2026
Same author

Biology-informed risk stratification of glioblastoma by integrating MRI-based intratumoral heterogeneity with clinical features: a multicenter validation study.

Experimental hematology & oncology·2026
Same author

Lanmodulin-Engineered Outer Membrane Vesicles for Synergistic Targeted Radio-Immunotherapy.

ACS nano·2026
Same journal

Body composition's effect on the bone-vascular axis of osteoporosis discovered in AI-based CT analysis of COPD patients.

European radiology·2026
Same journal

ESR Essentials: pelvic floor imaging-practice recommendations by the European Society of Urogenital Radiology.

European radiology·2026
Same journal

STIR or T2-Dixon? A false dilemma in musculoskeletal MRI.

European radiology·2026
Same journal

ESR Essentials: uterine cancers-practice recommendations by the European Society of Urogenital Radiology.

European radiology·2026
Same journal

Adjunctive quantification for more reproducible amyloid PET interpretation.

European radiology·2026
Same journal

APEX-NET: automated pancreatic evaluation network using early non-contrast CT.

European radiology·2026
See all related articles

Related Experiment Video

Updated: Oct 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

755

Accelerate gas diffusion-weighted MRI for lung morphometry with deep learning.

Caohui Duan1,2,3, He Deng1,2, Sa Xiao1,2

  • 1Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, 430071, People's Republic of China.

European Radiology
|July 13, 2021
PubMed
Summary
This summary is machine-generated.

Deep learning accelerates hyperpolarized 129Xe MRI for lung morphometry. This method significantly reduces scan time while maintaining accurate diffusion coefficient and morphometry parameter measurements.

Keywords:
Deep learningDiffusion magnetic resonance imagingLung

More Related Videos

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

763
Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods
05:07

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

Published on: September 6, 2024

523

Related Experiment Videos

Last Updated: Oct 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

755
Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

763
Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods
05:07

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

Published on: September 6, 2024

523

Area of Science:

  • Medical Imaging
  • Pulmonary Medicine
  • Artificial Intelligence

Background:

  • Multiple b-value gas diffusion-weighted MRI (DW-MRI) offers non-invasive lung morphometry assessment.
  • Long acquisition times limit patient tolerance and clinical utility.
  • Deep learning presents a potential solution for accelerating DW-MRI.

Purpose of the Study:

  • To accelerate multiple b-value gas DW-MRI for lung morphometry using deep learning.
  • To develop and evaluate a deep learning model for rapid image reconstruction.
  • To maintain quantitative accuracy of lung microstructural parameters.

Main Methods:

  • A deep cascade of residual dense network (DC-RDN) was developed for image reconstruction.
  • The DC-RDN was trained on retrospectively collected hyperpolarized 129Xe MRI data.
  • Performance was evaluated on both retrospective and prospective undersampled datasets.

Main Results:

  • DC-RDN achieved reconstruction of 64x64x5 slices within 7.2 ms.
  • Significant improvement in quantitative metrics compared to conventional methods (p < 0.05).
  • No significant difference in ADC and morphometry parameters between fully sampled and reconstructed images (p > 0.05).
  • Prospectively reduced breath-holding time from 17.8 to 4.7 s (acceleration factor of 4).

Conclusions:

  • DC-RDN effectively accelerates multiple b-value gas DW-MRI.
  • Accurate estimation of lung microstructural morphometry is maintained.
  • This acceleration enhances the clinical potential of hyperpolarized DW-MRI for studying lung diseases.