Online 4D Ultrasound-Guided Robotic Tracking Enables 3D Ultrasound Localization Microscopy With Large Tissue Displacements
Super-Resolution Ultrasound (SRUS) imaging through localising and tracking microbubbles, also known as Ultrasound localization Microscopy (ULM), has demonstrated reconstruction of microvascular structure and flow with sub-diffraction resolution, and its potential in a range of clinical applications. However, imaging organs with large tissue movements, such as those caused by respiration, presents substantial challenges. Existing methods often require breath holding to maintain accumulation accuracy, which limits data acquisition time and ULM image saturation. To improve image quality in the presence of large tissue movements, this study introduces an approach integrating high-frame-rate volumetric ultrasound with online precise robotic probe control. Tested on a microvasculature phantom with slow but large translation motions, up to 5 mm/s in speed and 20 mm in distance- twice the aperture size of the matrix array used, our method achieved real-time tracking of the moving phantom and imaging volume rate at 85 Hz, keeping majority of the target volume in the imaging field of view. ULM images of the moving cross channels in the phantom were successfully reconstructed in post-processing, demonstrating the feasibility of super-resolution imaging under large tissue motions. This represents a significant step towards ULM imaging of organs with large motion.
Authors
- Jipeng Yan (ORCID: https://orcid.org/0000-0002-0535-6052)
- Bingxue Wang (ORCID: https://orcid.org/0000-0003-4649-4598)
- Shusei Kawara (ORCID: https://orcid.org/0000-0002-7640-9510)
- Matthieu Toulemonde (ORCID: https://orcid.org/0000-0002-3191-8020)
- Ying Tan (ORCID: https://orcid.org/0000-0001-8495-0246)
- Honghai Liu (ORCID: https://orcid.org/0000-0002-2880-4698)
- Jingwen Zhu (ORCID: https://orcid.org/0000-0002-7954-6449)
- Meng-Xing Tang (ORCID: https://orcid.org/0000-0001-7686-425X)
- Qingyuan Tan (ORCID: https://orcid.org/0000-0002-6596-1625)
Institutions
- The University of Melbourne (AU)
- Imperial College London (GB)
- University of Portsmouth (GB)
Publication Details
- Journal
- IEEE Transactions on Medical Imaging
- Published
- 2025-05-19
- DOI
- https://doi.org/10.1109/tmi.2025.3571392
- Citations
- 1
- Primary Topic
- Surgical Simulation and Training
- Type
- article
- Field-Weighted Citation Impact
- 2.01
Funders
- NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
- Engineering and Physical Sciences Research Council