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Related Concept Videos

Ultrasonography01:17

Ultrasonography

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Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called...
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  11. An Adaptive Image Segmentation Approach For Tumor Region Identification In Ultrasound Images

An Adaptive Image Segmentation Approach for Tumor Region Identification in Ultrasound Images

Emmanuel Yangue, Yuxuan Li, Ashish Ranjan

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 3, 2025

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    View abstract on PubMed

    Summary
    This summary is machine-generated.

    This study introduces B-CLEAR, a new adaptive method for identifying tumor regions in ultrasound images. It improves accuracy and robustness in image-guided drug delivery by overcoming interference challenges.

    Area of Science:

    • Medical Imaging
    • Ultrasound Technology
    • Image-Guided Drug Delivery (IGDD)

    Background:

    • Accurate tumor region identification is crucial for image-guided drug delivery (IGDD).
    • Ultrasound imaging shows promise for IGDD, but interference poses challenges for automated region of interest (ROI) identification.
    • Current methods struggle with high interference levels in ultrasound images.

    Purpose of the Study:

    • To develop an ultrasound-specific image segmentation method for precise and reliable ROI identification.
    • To address the limitations of existing techniques in handling interference during ultrasound ROI detection.

    Main Methods:

    • Proposed a novel adaptive approach named B-CLEAR.
    • Employed a collaborative framework integrating gradient-based Boundary detection, feature-based Center Locating, and Edge-Assisted Region growing.

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  • Validated the method using a real-world colon tumor ultrasound image dataset.

    • Main Results:

    • The B-CLEAR method demonstrated superior performance in ROI identification compared to conventional segmentation algorithms.
    • The approach proved effective in handling interference inherent in ultrasound images.
    • Validation on a real-world dataset confirmed the method's capability.

    Conclusions:

    • B-CLEAR offers an accurate and robust solution for ROI identification in ultrasound images.
    • The developed method enhances the potential of ultrasound in image-guided drug delivery.
    • This work contributes a significant advancement in medical image segmentation for therapeutic applications.