The-Bodega: A Matlab Toolbox for Biologically Dynamic Microbubble Simulations on Realistic Hemodynamic Microvascular Graphs

• URL: http://arxiv.org/abs/2509.08149v1
• Date: Tue, 09 Sep 2025 21:14:04 GMT
• Title: The-Bodega: A Matlab Toolbox for Biologically Dynamic Microbubble Simulations on Realistic Hemodynamic Microvascular Graphs
• Authors: Stephen Alexander Lee, Alexis Leconte, Alice Wu, Jonathan Poree, Maxence Laplante-Berthier, Simon Desrocher, Pierre-Olivier Bouchard, Joshua Kinugasa, Samuel Mihelic, Andreas Linninger, Jean Provost,
• Abstract summary: The-Bodega is a Matlab-based toolbox for simulating Ultrasound Microscopy datasets.<n>It supports consistent consistent micro-to-ultrasound simulations across domains ranging from mouse brains to human hearts.<n>We demonstrate its versatility in applications including image quality assessment, motion analysis, and the simulation of novel ULM modalities.
• Score: 1.8686303208366433
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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