The super-resolution ultrasound microvessel imaging (SR-UMI) technique offers a promising solution to the challenge of achieving both high imaging resolution and deep penetration in biomedical imaging. By using ultrasound contrast microbubbles and super-resolution strategies similar to PALM and STORM, SR-UMI enhances ultrasound imaging resolution by tenfold while maintaining deep penetration. This technique can resolve capillary-scale blood vessels at depths greater than 10 cm and measure microvascular blood flow speeds as low as 1 mm/s. SR-UMI provides detailed structural and functional information about tissue microvasculature and is noninvasive, low-cost, and free of ionizing radiation. Despite its potential, SR-UMI faces challenges such as slow data acquisition and computationally intensive post-processing, which hinder its clinical translation.
This technology is a method of real-time Super-Resolution Ultrasound Microvessel Imaging (SR-UMI). Current SR-UMI requires hours of data post-processing, making it impractical for clinical, diagnostic applications. Implementing advances in deep learning and parallel computing enabled real-time microbubble signal extraction, separation, localization, tracking, and quantitative analysis and display. This technology has a wide range of clinical applications, including but not limited to, the diagnosis and characterization of a range of disorders (e.g., cancer, cardiovascular disease, and neurological diseases).
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