With growing interest in super-resolution ultrasound (SRUS) via ultrasound localization microscopy (ULM), a wide range of localization and tracking algorithms have emerged. To evaluate and compare these methods, a major community-driven effort was launched: the ULTRA-SR Challenge. This initiative brought together 38 algorithm submissions from 24 research groups, using realistically simulated ultrasound datasets that modeled microvascular flow and nonlinear bubble dynamics across clinical ultrasound frequencies. The challenge assessed both localization and tracking performance using six quantitative metrics, alongside expert evaluations on in vivo mouse brain and human lymph node data. The paper outlines the challenge structure, data generation, evaluation methods, and highlights the top-performing algorithms. All datasets, ground truths, and metrics have been made publicly available—providing the field with a valuable benchmarking resource to optimize methods, compare software, and understand current performance limits in SRUS.
https://orbit.dtu.dk/en/publications/ultra-sr-challenge-assessment-of-ultrasound-localization-and-trac
