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Related Concept Videos

Phase Contrast and Differential Interference Contrast Microscopy01:26

Phase Contrast and Differential Interference Contrast Microscopy

Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...

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Related Experiment Video

Updated: Jul 1, 2026

Imaging and Quantification of the Area of Fast-Moving Microbubbles Using a High-Speed Camera and Image Analysis
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An Inverse Method Using Cross-Spectral Matrix Fitting for Passive Cavitation Imaging.

Celestine Lachambre, Adrian Basarab, Jean-Christophe Bera

    IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
    |June 19, 2024
    PubMed
    Summary
    This summary is machine-generated.

    We improved passive cavitation imaging using a novel cross spectral matrix fitting (CMF) method. This technique enhances axial resolution and contrast-to-noise ratio for monitoring high-intensity focused ultrasound (HIFU) applications.

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    Area of Science:

    • Medical Imaging
    • Acoustics
    • Ultrasound Technology

    Background:

    • High-intensity focused ultrasound (HIFU) applications like sonoporation and drug delivery require monitoring of cavitation.
    • Passive acoustic mapping offers cavitation monitoring but suffers from poor axial resolution, unlike pulse-echo ultrasound.
    • Existing methods lack precise spatial localization of cavitation events.

    Purpose of the Study:

    • To enhance axial resolution in passive cavitation imaging.
    • To adapt the cross spectral matrix fitting (CMF) method for improved spatial mapping of cavitation.
    • To compare the performance of CMF with Elastic Net (CMF-ElNet) and sparse Total Variation (CMF-spTV) regularizations against existing techniques.

    Main Methods:

    • Developed an adapted cross spectral matrix fitting (CMF) method to solve an inverse problem for passive cavitation imaging.
    • Applied sparsity-promoting regularizations: Elastic Net (ElNet) and sparse Total Variation (spTV).
    • Validated the CMF methods using simulated and experimental data, comparing them to frequential delay-and-sum (DAS) and robust capon beamformer (RCB).

    Main Results:

    • CMF methods significantly improved axial resolution, achieving a 3x and 5x reduction in full width half maximum (FWHM) compared to RCB and DAS, respectively.
    • CMF-based approaches enhanced contrast-to-noise ratio (CNR) by over 15 dB in experimental conditions compared to RCB.
    • The sparse Total Variation (spTV) prior demonstrated superior performance for cloud-shaped cavitation sources.

    Conclusions:

    • The adapted CMF method offers a substantial improvement in axial resolution for passive cavitation imaging.
    • CMF-based techniques provide superior contrast and spatial accuracy for monitoring HIFU-induced cavitation.
    • Sparse regularization, particularly spTV, is effective for reconstructing complex cavitation patterns.