Search

Researchers at the Beckman Institute for Advanced Science and Technology have developed a new technique called LOCA-ULM to make ultrasound localization microscopy (ULM) more practical for clinical settings. ULM is an emerging diagnostic tool used for high-resolution microvascular imaging. The researchers used deep learning in the post-processing pipeline of ULM to improve imaging performance, processing speed, and sensitivity for functional ULM. Their method also demonstrated improved computational and microbubble localization performance and is adaptable to different microbubble concentrations. This advancement in ULM technology has the potential to make it more accessible and useful in medical and research fields. [Extracted from the article]

A recent report from the University of Illinois Urbana-Champaign discusses the use of ultrasound localization microscopy (ULM) to image deep tissue microvasculature by tracking microbubbles injected into the bloodstream. The researchers introduce a new technique called LOcalization with Awareness (LOCA)-ULM, which utilizes deep learning-based microbubble simulation and localization to improve the accuracy and efficiency of microbubble detection in high concentrations. LOCA-ULM outperformed conventional and deep learning-based methods in terms of accuracy and missing rate reduction. The researchers also demonstrated the superior performance of LOCA-ULM in functional ULM, where it increased the sensitivity of functional imaging in the rat brain. [Extracted from the article]