SIMUS: an open-source simulator for medical ultrasound imaging. Part I: theory & examples
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Abstract (arXiv)
Background and Objective: Computational ultrasound imaging has become a well-established methodology in the ultrasound community. Simulations of ultrasound sequences and images allow the study of innovative techniques in terms of emission strategy, beamforming, and probe design. There is a wide spectrum of software dedicated to ultrasound imaging, each having its specificities in its applications and the numerical method. Methods: We describe in this two-part paper a new ultrasound simulator (SIMUS) for MATLAB, which belongs to the MATLAB UltraSound Toolbox (MUST). The SIMUS software simulates acoustic pressure fields and radiofrequency RF signals for uniform linear or convex probes. SIMUS is an open-source software whose features are 1) ease of use, 2) time-harmonic analysis, 3) pedagogy. The main goal was to offer a comprehensive turnkey tool, along with a detailed theory for pedagogical and research purposes. Results: This article describes in detail the underlying linear theory of SIMUS and provides examples of simulated acoustic fields and ultrasound images. The accompanying article (part II) is devoted to the comparison of SIMUS with several software: Field II, k-Wave, FOCUS, and the Verasonics simulator. The MATLAB open codes for the simulator SIMUS are distributed under the terms of the GNU Lesser General Public License, and can be downloaded from https://www.biomecardio.com/MUST. Conclusions: The simulations described in the accompanying paper (Part II) show that SIMUS can be used for realistic simulations in medical ultrasound imaging.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Feb 2021.
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Citing papers per year: 2023: 1; 2024: 3; 2025: 2; 2026: 1.
7 papers.
- 2025Speckle2Self: Self-Supervised Ultrasound Speckle Reduction Without Clean Datacited by 9
- 2023Echocardiography video synthesis from end diastolic semantic map via diffusion modelcited by 7
- 2024Training-Free Condition Video Diffusion Models for single frame Spatial-Semantic Echocardiogram Synthesiscited by 6
- 2026Deep Learning Strain Estimation: Is Physics-Based Simulation the Solution?cited by 1
- 2024Pruning Sparse Tensor Neural Networks Enables Deep Learning for 3D Ultrasound Localization Microscopycited by 0
- 2024DeepSPV: A Deep Learning Pipeline for 3D Spleen Volume Estimation from 2D Ultrasound Imagescited by 0
- 2025UltraScatter: Ray-Based Simulation of Ultrasound Scatteringcited by 0
- 2026Deep Learning Strain Estimation: Is Physics-Based Simulation the Solution?27 May 2026
- 2025UltraScatter: Ray-Based Simulation of Ultrasound Scattering12 Oct 2025
- 2025Speckle2Self: Self-Supervised Ultrasound Speckle Reduction Without Clean Data9 Jul 2025
- 2024DeepSPV: A Deep Learning Pipeline for 3D Spleen Volume Estimation from 2D Ultrasound Images17 Nov 2024
- 2024Training-Free Condition Video Diffusion Models for single frame Spatial-Semantic Echocardiogram Synthesis6 Aug 2024
- 2024Pruning Sparse Tensor Neural Networks Enables Deep Learning for 3D Ultrasound Localization Microscopy14 Feb 2024
- 2023Echocardiography video synthesis from end diastolic semantic map via diffusion model11 Oct 2023