Structured Illumination for Super-Resolution Synthetic Aperture Ultrasound Imaging
In pulse-echo ultrasound (US) imaging, achieving higher lateral resolution requires increasing the transmit frequency, which results in penetration depth reduction. Given this trade-off between penetration depth and spatial resolution, we propose a method to resolve sub-diffraction scale structures in synthetic aperture (SA) US imaging. While structured illumination (SI) has previously been employed in US imaging, we introduce its application in SA US imaging to achieve superior resolution. In our approach, grating patterns are superimposed on the object to exploit high-frequency information, enhancing spatial resolution beyond conventional diffraction limits. However, a key challenge arises in applying SI to SA imaging: structured patterns cannot be directly generated using the single-element or multi-element transmissions inherent to SA. To overcome this, we introduce a novel method where pseudo-random plane wave (PW) illuminations are applied, followed by the retrieval of SA data from the acquired dataset. Five SA images corresponding to different SI pattern shifts are reconstructed and post-processed to generate a high-resolution structured illumination synthetic aperture (SISA) image. In-silico point spread function results reveal a 122% and 47% enhancement in lateral resolution when compared to conventional PW imaging (one-way focusing) and SA imaging (two-way focusing) for a grating pattern with a spatial frequency of 0.91 mm⁻¹. Furthermore, two additional in-silico studies were conducted to evaluate contrast and resolution under realistic conditions, demonstrating the superior performance of our proposed method compared to the previously reported acoustic SI technique. Additionally, two experiments validated the contrast and resolution performance of the proposed method in in-vitro conditions. The method possesses a wide range of applications, particularly in the detection of lesions demanding high spatial resolution.
Authors
- Vahid Amin Nili (ORCID: https://orcid.org/0000-0002-3804-6384)
- Seyed Masood Mostafavi (ORCID: https://orcid.org/0000-0003-1701-8154)
- Zahra Kavehvash (ORCID: https://orcid.org/0000-0002-7636-6100)
- Mahdi Shabany (ORCID: https://orcid.org/0000-0002-8625-9034)
- Mohammad Mehrmohammadi (ORCID: https://orcid.org/0000-0002-9264-9354)
Institutions
- Sharif University of Technology (IR)
- University of Rochester (US)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-09-05
- DOI
- https://doi.org/10.1109/jsen.2025.3604382
- Citations
- 3
- Primary Topic
- Ultrasound Imaging and Elastography
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- Iran National Science Foundation