PyMUST: an open-Source Python Library for the Simulation and Analysis of Ultrasound

Advances in ultrasonics, that have been translated to new techniques for ultrasound image acquisition and its post-processing, have been done not only by the use of hardware developments and circuitry, but also by means of computer software and techniques. Therefore, libraries for ultrasound signal processing and simulation have been proposed, some of them are publicly available for research use. One of them is Matlab Ultrasound Toolbox (MUST), which is open source and free to use, but it is implemented in a proprietary software that requires a license to run it. In this work, we present a reimplementation of MUST in the Python programming language, a free and popular interpreted programming language, which we named PyMUST.Our library is freely available in github (https://github.com/creatis-ULTIM/PyMUST), together with usage examples. It contains the processing functionalities for generating brightness-mode images from raw radiofrequencies, as well as motion estimation from sequential acquisitions, either from the radiofrequencies, using Doppler, or from beamformed images, using speckle tracking. It is also able to simulate virtual ultrasound acquisitions involving scattering reflections, using linear acoustics in the Fourier space.The main uses of this library are twofold. First, while in the past most of the processing steps for reconstructing images from the raw signals was done using dedicated electronics, nowadays it can be done using software. This allows to propose new improvements to the postprocessing more easily, as there is no need to build a physical processing circuit, but it is enough to develop a new software function. Secondly, it is possible to do in-silico experiments simulating ultrasound acoustics, thus it is possible to optimise the probe characteristics, as well as verify improvements in a variety of settings that would require prepare physical phantoms and/or transducers.

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Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1109/uffc-js60046.2024.10793881
Citations
3
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.62
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article

PyMUST: an open-Source Python Library for the Simulation and Analysis of Ultrasound

Damien Garcia, Gabriel Bernardino
3 citations
Soil Moisture and Remote Sensing
0.62
article

PyMUST: an open-Source Python Library for the Simulation and Analysis of Ultrasound

Damien Garcia, Gabriel Bernardino
article en
3 citations

Abstract

Advances in ultrasonics, that have been translated to new techniques for ultrasound image acquisition and its post-processing, have been done not only by the use of hardware developments and circuitry, but also by means of computer software and techniques. Therefore, libraries for ultrasound signal processing and simulation have been proposed, some of them are publicly available for research use. One of them is Matlab Ultrasound Toolbox (MUST), which is open source and free to use, but it is implemented in a proprietary software that requires a license to run it. In this work, we present a reimplementation of MUST in the Python programming language, a free and popular interpreted programming language, which we named PyMUST.Our library is freely available in github (https://github.com/creatis-ULTIM/PyMUST), together with usage examples. It contains the processing functionalities for generating brightness-mode images from raw radiofrequencies, as well as motion estimation from sequential acquisitions, either from the radiofrequencies, using Doppler, or from beamformed images, using speckle tracking. It is also able to simulate virtual ultrasound acquisitions involving scattering reflections, using linear acoustics in the Fourier space.The main uses of this library are twofold. First, while in the past most of the processing steps for reconstructing images from the raw signals was done using dedicated electronics, nowadays it can be done using software. This allows to propose new improvements to the postprocessing more easily, as there is no need to build a physical processing circuit, but it is enough to develop a new software function. Secondly, it is possible to do in-silico experiments simulating ultrasound acoustics, thus it is possible to optimise the probe characteristics, as well as verify improvements in a variety of settings that would require prepare physical phantoms and/or transducers.

Université Claude Bernard Lyon 1 (FR), Centre National de la Recherche Scientifique (FR), Inserm (FR), Universitat Pompeu Fabra (ES), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (FR), Institut National des Sciences Appliquées de Lyon (FR)
Openalex Percentile: Top 34%
Soil Moisture and Remote Sensing
0.62
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