Vortex-encoded full-waveform inversion-based ultrasound computed tomography
Ultrasound imaging of musculoskeletal tissue has long been a challenge. As a novel medical ultrasound computed tomography (UCT) technique, full-waveform inversion (FWI) provides a promising solution for musculoskeletal imaging with high spatial resolution. However, FWI suffers from a substantial computational burden, primarily due to the multiple wavefield calculations involved in the inversion process, especially when dealing with a large number of sources. In order to minimize the number of wavefield calculations, we propose a source encoding technology for musculoskeletal FWI. In detail, based on the ring-shaped array within the UCT configuration, a novel vortex encoding strategy is developed and applied to FWI. Given the orthogonal properties of acoustic vortices, this strategy effectively mitigates the cross talk artifacts between the encoding sources. This vortex-encoded full-waveform inversion (VE-FWI) significantly reduces computation load by an order of magnitude compared to the conventional FWI. Besides, the vortex encoding strategy enhances the quality of reconstructed images, with a 2.9% increase in peak signal-to-noise ratio and a 4.7% increase in structure similarity index measure compared to other traditional encoding strategies. VE-FWI not only accelerates musculoskeletal UCT but also maintains high imaging quality, presenting a promising solution for practical applications with both accuracy and computational efficiency.
Authors
- Guo-Liang Ma (ORCID: https://orcid.org/0000-0002-7002-8442)
- Kailiang Xu (ORCID: https://orcid.org/0000-0002-1819-4101)
- Chenchen Zhou (ORCID: https://orcid.org/0000-0001-9948-9827)
- Ying Li (ORCID: https://orcid.org/0000-0002-4318-591X)
Institutions
- Fudan University (CN)
Publication Details
- Journal
- The Journal of the Acoustical Society of America
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1121/10.0036366
- Citations
- 1
- Primary Topic
- Seismic Imaging and Inversion Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.87
Funders
- National Natural Science Foundation of China