Quantitative Ultrasound Through Strongly Scattering Tissues

Abstract: My research focuses on increasing the specificity of ultrasound imaging by developing quantitative ultrasound (QUS) approaches that extract physically meaningful parameters from backscattered wavefields. 
These methods have the potential to enable functional assessment of highly heterogeneous tissues, including tumors, lung, and bone. This quantitative ultrasound framework for characterizing complex tissues has applications ranging from cancer imaging to lung monitoring and intraoperative guidance. Across these applications, we combine full synthetic aperture acquisitions with scattering theory to interrogate tissue microstructure, vascular organization, and porosity.
After a general presentation of the methods, we present the study of the scattering behavior of signals backscattered from microbubbles used to image tumor-related angiogenesis. We show that diffusion-based metrics can serve as biomarkers of neovascular density, providing information that complements conventional acoustic angiography, and that has the potential to predict tumor aggressiveness.
We also investigate diffusion-based metrics for characterizing complex lung-mimicking media in the presence of aberrating layers. We compare two complementary strategies: incoherent backscattering using virtual-source beamforming, and phase-enhanced coherent backscattering. Our results indicate that these approaches can probe the properties of porous tissue through overlying muscle and fat, opening new possibilities for quantitative in vivo assessment of organs such as the lung and bone.
Finally, we assess scattering- and entropy-based methods for detecting lung nodules for surgery guidance. We examine how lung aeration influences wave memory, penetration depth, and the sensitivity of each method. This comparative analysis highlights key trade-offs and guides the development of more robust strategies for real-time ultrasound guidance during lung nodule localization in surgery.

‼️ Le séminaire peut être suivi en ligne svia le lien : https://univ-amu-fr.zoom.us/j/95011527683?pwd=bTeNvaaZY75buaa7bRL0pcucXSASm7.1

Le mardi 17 mars 2026 à 11h00 / Amphithéâtre François Canac, LMA

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