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Related Experiment Video

Updated: Jan 31, 2026

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
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SEGUE: A Speedy rEgion-Growing Algorithm for Unwrapping Estimated Phase.

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    A new algorithm, Speedy Region-Growing for Unwrapping Estimated phase (SEGUE), significantly accelerates magnetic resonance imaging (MRI) phase unwrapping. SEGUE achieves results comparable to the gold standard PRELUDE but is up to 70 times faster, improving MRI data processing efficiency.

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    Area of Science:

    • Medical Imaging
    • Computational Imaging
    • Biophysics

    Background:

    • Magnetic resonance imaging (MRI) phase data is crucial for quantitative susceptibility mapping and distortion correction in functional and diffusion MRI.
    • Phase images are inherently wrapped within a 2π range, necessitating unwrapping for accurate interpretation.
    • The current gold standard for 3D MRI phase unwrapping, PRELUDE, suffers from computationally intensive processing times.

    Purpose of the Study:

    • To develop a faster and efficient algorithm for MRI phase unwrapping.
    • To compare the performance and accuracy of the new algorithm against the established PRELUDE method.
    • To address and mitigate chemical-shift-induced errors in specific anatomical regions.

    Main Methods:

    • Development of the Speedy Region-Growing algorithm for Unwrapping Estimated phase (SEGUE), incorporating acceleration techniques.
    • Comparative analysis of SEGUE and PRELUDE using numerical phantoms and in vivo MRI data from brain, head and neck, and pelvic regions.
    • Implementation of separate fat and water masking strategies to resolve chemical-shift artifacts.

    Main Results:

    • SEGUE generated unwrapped phase maps virtually identical to those produced by PRELUDE.
    • SEGUE demonstrated significant speed improvements, being 1.5 to 70 times faster than PRELUDE, particularly in challenging datasets.
    • The fat and water masking approach effectively eliminated chemical-shift-induced errors in head/neck and pelvic images.

    Conclusions:

    • SEGUE offers a computationally efficient and accurate alternative for MRI phase unwrapping.
    • The algorithm's speed enhancement has practical implications for reducing MRI data processing times.
    • SEGUE's general applicability extends beyond MRI, offering potential use in other imaging modalities.