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: Jan 9, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

996

EAMF: An Entropy-enhanced Attention-based Ensemble Metric Few-Shot Learning for MRI Image Classification.

Ramesh Naidu Laveti, Jaya Sreevalsan-Nair, T K Srikanth

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 3, 2025
    PubMed
    Summary
    This summary is machine-generated.

    Related Concept Videos

    Magnetic Resonance Imaging01:24

    Magnetic Resonance Imaging

    8.9K
    Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
    8.9K

    You might also read

    Related Articles

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

    Sort by
    Same author

    Addendum: Evaluating Characteristics and Quality of Mental Health Apps Available in App Stores for Indian Users: Systematic App Search and Review.

    JMIR mHealth and uHealth·2026
    Same author

    What Youth Write About and Seek in an Anonymized Online Peer Support Forum: Insights from India.

    International journal of environmental research and public health·2026
    Same author

    Technology for Mental Health: Reflections on Scope and Future Directions in Institutes of Higher Education in India.

    Online journal of public health informatics·2025
    Same author

    Authors' Reply: Methodological Considerations in Evaluating Mental Health Apps: Ensuring Reliability and Patient Safety.

    JMIR mHealth and uHealth·2025
    Same author

    The PAthways to Resilience And Mental health (PARAM) project: protocol for a multi-site developmental cohort in India.

    BMC psychiatry·2025
    Same author

    Evaluating Characteristics and Quality of Mental Health Apps Available in App Stores for Indian Users: Systematic App Search and Review.

    JMIR mHealth and uHealth·2025
    Same journal

    Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same journal

    AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same journal

    Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same journal

    Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same journal

    Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    Same journal

    A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
    See all related articles

    This study introduces Entropy-enhanced Attention-based Ensemble Metric Few-Shot Learning (EAMF) to improve MRI image classification with limited data. EAMF enhances feature discrimination, outperforming existing deep learning models on MRI datasets.

    Area of Science:

    • Medical Imaging
    • Machine Learning
    • Computer Vision

    Background:

    • Large-scale labeled datasets are crucial but challenging to obtain for MRI image classification, especially for rare diseases or due to privacy concerns.
    • Few-Shot Learning (FSL) addresses data scarcity by enabling classification with minimal training examples.
    • Metric-based FSL (MFSL) relies on learning discriminative metrics but struggles with effective intra-class and inter-class feature variations.

    Purpose of the Study:

    • To propose a novel Few-Shot Learning (FSL) method, Entropy-enhanced Attention-based Ensemble Metric FSL (EAMF), to enhance class discrimination in MRI image classification.
    • To improve the effectiveness of deep feature embeddings in distinguishing between classes despite limited data.
    • To evaluate the performance of the proposed EAMF method against existing deep learning models.

    Related Experiment Videos

    Last Updated: Jan 9, 2026

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    996

    Main Methods:

    • Developed EAMF, incorporating patch-wise image entropy to create an additional entropy-feature vector.
    • Concatenated entropy-feature vectors with backbone network embeddings for an ensemble approach.
    • Implemented an attention mechanism to weight embeddings based on class representativeness and evaluated three distance metrics.

    Main Results:

    • The proposed EAMF method demonstrated superior performance in MRI image classification compared to standalone deep learning models.
    • The integration of entropy-features and the attention-based ensemble significantly improved class discrimination.
    • Experimental results on two MRI datasets validated the effectiveness of the EAMF approach.

    Conclusions:

    • EAMF effectively addresses the limitations of traditional MFSL by enhancing feature embeddings for better class discrimination.
    • The novel approach shows significant promise for improving MRI image classification in data-scarce scenarios.
    • EAMF offers a robust solution for medical image analysis where data availability is a constraint.