부산대학교 도서관

The development of acoustic super-resolution (SR) techniques, and specifically of ultrasound localization microscopy (ULM), in recent years has enabled massive advances toward high resolution, non-invasive imaging and characterization of the microvasculature. However, ULM is relies on repeated isolation of individual ultrasound contrast agents (UCAs) which act as effective point scatterers. This cumulative technique incurs an inherent compromise between the spatial and temporal resolution of the resulting images. Thus, it is of primary importance that sensitive and specific methods for the localization of these targets are refined to realize the full potential of SR techniques. Here, we apply morphological image processing techniques to the challenge problem datasets to demonstrate their efficacy and efficiency for localization and subsequent tracking.