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 Experiment Videos

Fast single image super-resolution using estimated low-frequency k-space data in MRI.

Jianhua Luo1, Zhiying Mou2, Binjie Qin3

  • 1School of Aeronautics and Astronautics, Shanghai Jiao Tong University, 200240, China.

Magnetic Resonance Imaging
|April 4, 2017
PubMed
Summary

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

Efficacy of real-time artificial intelligence-aid endoscopic ultrasonography diagnostic system in discriminating gastrointestinal stromal tumors and leiomyomas: a multicenter diagnostic study.

EClinicalMedicine·2024
Same author

Locating X-Ray Coronary Angiogram Keyframes via Long Short-Term Spatiotemporal Attention With Image-to-Patch Contrastive Learning.

IEEE transactions on medical imaging·2023
Same author

Editorial: Cerebral vessel extraction-from image acquisition to machine learning.

Frontiers in neuroscience·2022
Same author

Robust PCA Unrolling Network for Super-Resolution Vessel Extraction in X-Ray Coronary Angiography.

IEEE transactions on medical imaging·2022
Same author

An assessment of how the anterior cerebral artery anatomy impacts ACoA aneurysm formation based on CFD analysis.

British journal of neurosurgery·2020
Same author

Sequential vessel segmentation via deep channel attention network.

Neural networks : the official journal of the International Neural Network Society·2020
Same journal

Repeatability of an MRI protocol for generating habitats based on cellularity, perfusion, and hypoxia in a murine model of glioma.

Magnetic resonance imaging·2026
Same journal

Association between CMR-derived pulmonary artery pulse wave velocity and pulmonary risk factors: the multi-ethnic study of atherosclerosis COPD study.

Magnetic resonance imaging·2026
Same journal

Systematic comparison of MPRAGE and BRAVO T1-weighted MRI pulse sequences and brain morphometry in high-risk young adults.

Magnetic resonance imaging·2026
Same journal

Foot dynamic contrast-enhanced MRI for assessing microcirculatory changes after endovascular therapy in peripheral artery disease: A prospective pilot study.

Magnetic resonance imaging·2026
Same journal

Reconstruction of MRI from undersampled k-spaces of double-contrast volume acquisitions using deep neural networks.

Magnetic resonance imaging·2026
Same journal

Radiofrequency-induced heating safety of brain MRI scans at 7 T in the presence of a shoulder implant.

Magnetic resonance imaging·2026
See all related articles
This summary is machine-generated.

This study introduces a fast and robust single image super-resolution (SR) method for magnetic resonance imaging (MRI). The novel approach enhances image quality and spatial consistency, outperforming existing methods.

Area of Science:

  • Medical Imaging
  • Image Processing
  • Computational Science

Background:

  • Single image super-resolution (SR) is crucial for enhancing image detail in various fields.
  • Technical limitations often hinder practical application of SR methods.
  • Magnetic resonance imaging (MRI) benefits significantly from improved image resolution.

Purpose of the Study:

  • To develop a simple, rapid, and robust single image SR method specifically for MRI.
  • To address the practical challenges in obtaining high-resolution MR images.
  • To improve the diagnostic value of MR imaging through enhanced resolution.

Main Methods:

  • A novel SR method based on the k-space link between low-resolution (LR) and super-resolved (SR) images.
  • Estimation of low-frequency k-space data from a single LR MR image.
Keywords:
Image interpolationMagnetic resonance imagingSuper-resolutionk-Space data

Related Experiment Videos

  • Reconstruction of the SR image using estimated low-frequency and zero-filled high-frequency k-space data.

    • Main Results:

    • The proposed SR method demonstrated superior robustness and performance compared to existing methods (EGNI, ZF, TV).
    • Achieved higher Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) values.
    • Exhibited reduced artifacts (ringing, blocking) and superior spatial consistency across slices.

    Conclusions:

    • A fast, robust, and efficient single image SR method for clinical MRI was successfully developed.
    • The method effectively enhances image quality and spatial consistency in the inter-slice dimension.
    • This technique offers a valuable tool for improving MR image analysis and interpretation.