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 Video

Updated: Aug 16, 2025

Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States
06:25

Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States

Published on: January 19, 2024

1.1K

Multi-weight respecification of scan-specific learning for parallel imaging.

Hui Tao1, Wei Zhang1, Haifeng Wang2

  • 1Department of Electronic Information Engineering, Nanchang University, Nanchang 330031, China.

Magnetic Resonance Imaging
|December 25, 2022
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

Enantioselective Radical Ring-Opening Cyanation of Oxime Esters by Dual Photoredox and Copper Catalysis.

Organic letters·2019
Same author

ACCELERATING MAGNETIC RESONANCE IMAGING VIA DEEP LEARNING.

Proceedings. IEEE International Symposium on Biomedical Imaging·2019
Same author

Technical note: Development and application of KASP assays for rapid screening of 8 genetic defects in Holstein cattle.

Journal of dairy science·2019
Same author

Sesquiterpenes and diterpenes from Euphorbia thymifolia.

Fitoterapia·2019
Same author

Glechomanamides A-C, Germacrane Sesquiterpenoids with an Unusual Δ<sup>8</sup>-7,12-Lactam Moiety from <i>Salvia scapiformis</i> and Their Antiangiogenic Activity.

Journal of natural products·2019
Same author

Parameter optimization framework on wave gradients of Wave-CAIPI imaging.

Magnetic resonance in medicine·2019

A new multi-weight method (MW-RAKI) enhances magnetic resonance imaging reconstruction, improving performance at high acceleration rates. This robust artificial neural network approach offers superior noise resilience compared to traditional methods.

Area of Science:

  • Medical Imaging
  • Magnetic Resonance Imaging (MRI)
  • Image Reconstruction

Background:

  • Parallel imaging accelerates MRI acquisition but traditional methods amplify noise.
  • Robust Artificial Neural Network for k-space Interpolation (RAKI) offers better noise resilience but struggles with high acceleration and requires extensive training data.
  • Existing methods face limitations in noise handling and data efficiency for accelerated MRI.

Purpose of the Study:

  • To develop an improved reconstruction method for parallel imaging in MRI.
  • To enhance noise resilience and performance at high acceleration rates.
  • To reduce the need for extensive autocalibration signals in neural network-based reconstruction.

Main Methods:

  • Proposed a multi-weight method (MW-RAKI) applying multiple weighting matrices to under-sampled MRI data.
Keywords:
Imaging reconstructionK-spaceMulti-weight respecificationParallel magnetic resonance imagingScan-specific learning

More Related Videos

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
09:30

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Published on: December 18, 2016

19.6K
Dual Raster-Scanning Photoacoustic Small-Animal Imager for Vascular Visualization
07:14

Dual Raster-Scanning Photoacoustic Small-Animal Imager for Vascular Visualization

Published on: July 15, 2020

4.2K

Related Experiment Videos

Last Updated: Aug 16, 2025

Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States
06:25

Author Spotlight: Comparative Imaging of Neural Activity in Awake and Freely Moving States

Published on: January 19, 2024

1.1K
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
09:30

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Published on: December 18, 2016

19.6K
Dual Raster-Scanning Photoacoustic Small-Animal Imager for Vascular Visualization
07:14

Dual Raster-Scanning Photoacoustic Small-Animal Imager for Vascular Visualization

Published on: July 15, 2020

4.2K
  • Integrated multiple weighting matrices into a residual RAKI framework (MW-rRAKI).
  • Evaluated reconstruction performance against alternative methods, particularly at high acceleration factors.

    • Main Results:

    • MW-RAKI and MW-rRAKI demonstrated superior reconstruction performance compared to RAKI and rRAKI, especially at high acceleration rates.
    • With only 12.5% k-space data, MW-RAKI and MW-rRAKI achieved PSNR improvements of approximately 3 dB and 4 dB over RAKI and rRAKI, respectively.
    • The multi-weight strategy effectively reduced noise influence and increased data constraints.

    Conclusions:

    • MW-RAKI and MW-rRAKI represent significant advancements in accelerated MRI reconstruction.
    • These methods offer improved image quality and efficiency, particularly in scenarios with limited acquired data and high acceleration.
    • The proposed techniques address key limitations of existing parallel imaging reconstruction algorithms.