🤖 AI Summary
This study addresses the lack of ground-truth hemodynamic benchmark data for ultrasound localization microscopy (ULM) algorithms. Methodologically, we present the first open-source, organ-agnostic ULM simulation platform built in MATLAB. It features a flexible vascular structure modeling framework and introduces, for the first time, a sequential Monte Carlo simulation integrating pulsatile flow with Poiseuille flow to accurately capture microbubble biodynamics in tissues such as mouse brain and human heart. The platform incorporates SVD-based spatiotemporal filtering and Fourier ring correlation to enable fully automated, end-to-end generation—from microbubble trajectories to RF signals to ULM images—with CPU/GPU parallel acceleration. Its key contribution is a high-fidelity digital phantom dataset that enables cross-organ ULM algorithm evaluation, motion artifact analysis, myocardial reconstruction in beating hearts, and neurovascular coupling modeling—thereby significantly improving validation rigor and accelerating development of super-resolution ultrasound imaging methods and novel modalities.
📝 Abstract
The-Bodega is a Matlab-based toolbox for simulating ground-truth datasets for Ultrasound Localization Microscopy (ULM)-a super resolution imaging technique that resolves microvessels by systematically tracking microbubbles flowing through the microvasculature. The-Bodega enables open-source simulation of stochastic microbubble dynamics through anatomically complex vascular graphs and features a quasi-automated pipeline for generating ground-truth ultrasound data from simple vascular inputs. It incorporates sequential Monte Carlo simulations augmented with Poiseuille flow distributions and dynamic pulsatile flow. A key novelty of our framework is its flexibility to accommodate arbitrary vascular architectures and benchmark common ULM algorithms, such as Fourier Ring Correlation and Singular Value Decomposition (SVD) spatiotemporal filtering, on realistic hemodynamic digital phantoms. The-Bodega supports consistent microbubble-to-ultrasound simulations across domains ranging from mouse brains to human hearts and automatically leverages available CPU/GPU parallelization to improve computational efficiency. We demonstrate its versatility in applications including image quality assessment, motion artifact analysis, and the simulation of novel ULM modalities, such as capillary imaging, myocardial reconstruction under beating heart motion, and simulating neurovascular evoked responses.