Deep Learning Based Microbubble Localization for Fast and Robust Ultrasound Localization Microscopy

Ultrasound localization microscopy (ULM) is a recently developed technique that addresses the resolution-penetration trade-off of ultrasound. However, its clinical application was limited by localization performance. In this study, we propose to improve the localization performance of ULM with a deep learning based localization technique that uses Field-II simulation and RF data.