In ultrasound localization microscopy (ULM), accurately tracking isolated microbubbles (MBs) is crucial for reconstructing high-quality vascular images. Traditional tracking approaches—such as the Hungarian algorithm and the Kalman filter—each offer unique strengths but also have inherent limitations.
In this work, Mostafa Amin Naji introduces a fusion of both tracking methods to leverage their complementary advantages. The combined approach enhances the visualization of microvascular density and flow velocity, improving both the precision and robustness of ULM imaging.
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