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Ultrasound contrast enhanced imaging has seen widespread uptake in researchand clinical diagnostic imaging. This includes applications such as vector flowimaging, functional ultrasound and super-resolution Ultrasound LocalizationMicroscopy (ULM). All of these require testing and validation duringdevelopment of new algorithms with ground truth data. In this work we present acomprehensive simulation platform BUbble Flow Field (BUFF) that generatescontrast enhanced ultrasound images in vascular tree geometries with realisticflow characteristics and validation algorithms for ULM. BUFF allows complexmicro-vascular network generation of random and user-defined vascular networks.Blood flow is simulated with a fast Computational Fluid Dynamics (CFD) solverand allows arbitrary input and output positions and custom pressures. Theacoustic field simulation is combined with non-linear Microbubble (MB) dynamicsand simulates a range of point spread functions based on user-defined MBcharacteristics. The validation combines both binary and quantitative metrics.BFF's capacity to generate and validate user-defined networks is demonstratedthrough its implementation in the Ultrasound Localisation and TRackingAlgorithms for Super Resolution (ULTRA-SR) Challenge at the InternationalUltrasonics Symposium (IUS) 2022 of the Institute of Electrical and ElectronicsEngineers (IEEE). The ability to produce ULM images, and the availability of aground truth in localisation and tracking enables objective and quantitativeevaluation of the large number of localisation and tracking algorithmsdeveloped in the field. BUFF can also benefit deep learning based methods byautomatically generating datasets for training. BUFF is a fully comprehensivesimulation platform for testing and validation of novel ULM techniques and isopen source.

BUbble Flow Field: a Simulation Framework for Evaluating Ultrasound Localization Microscopy Algorithms