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Related Experiment Video

Updated: May 13, 2026

Training Dogs for Awake, Unrestrained Functional Magnetic Resonance Imaging
07:59

Training Dogs for Awake, Unrestrained Functional Magnetic Resonance Imaging

Published on: October 13, 2019

Structure-Semantic Guided MRI-to-PET Synthesis with Spatial-Frequency Discriminator.

Xin Song, Ke Wang, Meimei Li

    IEEE Journal of Biomedical and Health Informatics
    |May 11, 2026
    PubMed
    Summary

    This study introduces a new AI method to create realistic PET scans from MRI data, improving Alzheimer's disease diagnosis. This approach enhances medical imaging accessibility and accuracy for early detection.

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    Area of Science:

    • Medical Imaging
    • Artificial Intelligence
    • Neuroscience

    Background:

    • Multi-modal imaging, combining MRI and PET, is crucial for Alzheimer's disease (AD) diagnosis and monitoring.
    • PET imaging, while valuable, faces limitations due to cost, radiation, and availability.

    Purpose of the Study:

    • To develop an adversarial framework for synthesizing PET images from structural MRI.
    • To enhance early AD diagnosis and progression monitoring by overcoming PET limitations.

    Main Methods:

    • A novel framework incorporating Multi-scale Structural Representation Injection (MSRI) and Adaptive Semantic Residual Fusion (ASRF) modules.
    • Utilized hierarchical anatomical encoding, axis-aware attention, dual-attention gating, and Transformer representations.
    • Employed a Direction-Aware Spatial-Frequency Discriminator (DASFD) with reconstruction-guided priors for anatomical fidelity.

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    Simultaneous PET/MRI Imaging During Mouse Cerebral Hypoxia-ischemia
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    Simultaneous PET/MRI Imaging During Mouse Cerebral Hypoxia-ischemia

    Published on: September 20, 2015

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    Last Updated: May 13, 2026

    Training Dogs for Awake, Unrestrained Functional Magnetic Resonance Imaging
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    Published on: October 13, 2019

    Simultaneous PET/MRI Imaging During Mouse Cerebral Hypoxia-ischemia
    10:35

    Simultaneous PET/MRI Imaging During Mouse Cerebral Hypoxia-ischemia

    Published on: September 20, 2015

    Main Results:

    • The proposed method successfully synthesized high-fidelity PET images from MRI.
    • Achieved high quantitative accuracy with SSIM of 90.66% and PSNR of 26.35 dB.
    • Demonstrated superior performance over existing methods in both accuracy and visual realism.

    Conclusions:

    • The developed AI framework effectively generates plausible PET representations from MRI, addressing key limitations of PET imaging.
    • This approach holds significant potential for improving the accessibility and accuracy of Alzheimer's disease diagnosis and management.