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

[Review article for breast imaging & treatment]

Isao Muro, Naruo Nishiki, Akiko Hattori

    Nihon Hoshasen Gijutsu Gakkai Zasshi
    |September 6, 2003
    PubMed
    Summary

    No abstract available in PubMed .

    Related Experiment Videos

    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

    Using Deep Learning to Simultaneously Reduce Noise and Motion Artifacts in Brain MR Imaging.

    Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine·2025
    Same author

    Development and validation of an algorithm for identifying patients undergoing dialysis from patients with advanced chronic kidney disease.

    Clinical and experimental nephrology·2025
    Same author

    Factors associated with awareness of chronic kidney disease, and impact of awareness on renal prognosis.

    Clinical and experimental nephrology·2024
    Same author

    Metabolomic analysis of serum samples from a clinical study on ipragliflozin and metformin treatment in Japanese patients with type 2 diabetes: Exploring human metabolites associated with visceral fat reduction.

    Pharmacotherapy·2023
    Same author

    [[MRI] 1. The History of Image Reconstraction for MRI].

    Nihon Hoshasen Gijutsu Gakkai zasshi·2023
    Same author

    Evaluation of motion artefact reduction depending on the artefacts' directions in head MRI using conditional generative adversarial networks.

    Scientific reports·2023