Samuel Beuret
Postdoctoral Scholar, Radiology
Bio
I received the B.Sc., M.Sc., and Ph.D. degrees in Electrical Engineering from the École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, in 2016, 2019, and 2024, respectively. After working as an Ultrasound Engineer at E-Scopics, Aix-en-Provence, France, I joined the Ultrasound Imaging and Instrumentation Lab of the Department of Radiology as a Postdoctoral Scholar in 2025. My research interests include signal processing, inverse problems, and probabilistic modeling applied to pulse-echo ultrasound imaging. My current work focuses on improving pulse-echo speed-of-sound imaging and distributed aberration correction.
All Publications
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A Refraction-Aware Pulse-Echo Speed-of-Sound Imaging Method for Convex Transducers
IEEE. 2025
View details for DOI 10.1109/IUS62464.2025.11201342
View details for Web of Science ID 001719884800078
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Inverse Problem for Joint Deconvolution, Despeckling, and Source Separation in B-Mode Ultrasound
IEEE. 2025
View details for DOI 10.1109/IUS62464.2025.11201400
View details for Web of Science ID 001719884800136
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Windowed Radon Transform for Robust Speed-of-Sound Imaging With Pulse-Echo Ultrasound
IEEE TRANSACTIONS ON MEDICAL IMAGING
2024; 43 (4): 1579-1593
Abstract
In recent years, methods estimating the spatial distribution of tissue speed of sound with pulse-echo ultrasound are gaining considerable traction. They can address limitations of B-mode imaging, for instance in diagnosing fatty liver diseases. Current state-of-the-art methods relate the tissue speed of sound to local echo shifts computed between images that are beamformed using restricted transmit and receive apertures. However, the aperture limitation affects the robustness of phase-shift estimations and, consequently, the accuracy of reconstructed speed-of-sound maps. Here, we propose a method based on the Radon transform of image patches able to estimate local phase shifts from full-aperture images. We validate our technique on simulated, phantom and in-vivo data acquired on a liver and compare it with a state-of-the-art method. We show that the proposed method enhances the stability to changes of beamforming speed of sound and to a reduction of the number of insonifications. In particular, the deployment of pulse-echo speed-of-sound estimation methods onto portable ultrasound devices can be eased by the reduction of the number of insonifications allowed by the proposed method.
View details for DOI 10.1109/TMI.2023.3343918
View details for Web of Science ID 001196733400005
View details for PubMedID 38109237
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An Inverse-Problem Approach to the Estimation of Despeckled and Deconvolved Images From Radio-Frequency Signals in Pulse-Echo Ultrasound
IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING
2024; 10: 1191-1206
View details for DOI 10.1109/TCI.2024.3441234
View details for Web of Science ID 001302493600002
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Windowed Radon Transform and Tensor Rank-1 Decomposition for Adaptive Beamforming in Ultrafast Ultrasound
IEEE TRANSACTIONS ON MEDICAL IMAGING
2024; 43 (1): 135-148
Abstract
Ultrafast ultrasound has recently emerged as an alternative to traditional focused ultrasound. By virtue of the low number of insonifications it requires, ultrafast ultrasound enables the imaging of the human body at potentially very high frame rates. However, unaccounted for speed-of-sound variations in the insonified medium often result in phase aberrations in the reconstructed images. The diagnosis capability of ultrafast ultrasound is thus ultimately impeded. Therefore, there is a strong need for adaptive beamforming methods that are resilient to speed-of-sound aberrations. Several of such techniques have been proposed recently but they often lack parallelizability or the ability to directly correct both transmit and receive phase aberrations. In this article, we introduce an adaptive beamforming method designed to address these shortcomings. To do so, we compute the windowed Radon transform of several complex radio-frequency images reconstructed using delay-and-sum. Then, we apply to the obtained local sinograms weighted tensor rank-1 decompositions and their results are eventually used to reconstruct a corrected image. We demonstrate using simulated and in-vitro data that our method is able to successfully recover aberration-free images and that it outperforms both coherent compounding and the recently introduced SVD beamformer. Finally, we validate the proposed beamforming technique on in-vivo data, resulting in a significant improvement of image quality compared to the two reference methods.
View details for DOI 10.1109/TMI.2023.3295657
View details for Web of Science ID 001158081600038
View details for PubMedID 37450358
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Using Windowed Radon Transform to Measure Local Coherence Independently of Speed-of-Sound Variations in Plane-Wave Imaging
IEEE. 2024
View details for DOI 10.1109/UFFC-JS60046.2024.10793873
View details for Web of Science ID 001428150100335
https://orcid.org/0000-0001-6558-0892