Neural Born Series Operator for Biomedical Ultrasound Computed Tomography

Zhijun Zeng, Yihang Zheng, Youjia Zheng, Yubing Li, Zuoqiang Shi +1 more
12/25/2023
eess.IVcs.CVcs.LG

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Abstract

Ultrasound Computed Tomography (USCT) provides a radiation-free option for high-resolution clinical imaging. Despite its potential, the computationally intensive Full Waveform Inversion (FWI) required for tissue property reconstruction limits its clinical utility. This paper introduces the Neural Born Series Operator (NBSO), a novel technique designed to speed up wave simulations, thereby facilitating a more efficient USCT image reconstruction process through an NBSO-based FWI pipeline. Thoroughly validated on comprehensive brain and breast datasets, simulated under experimental USCT conditions, the NBSO proves to be accurate and efficient in both forward simulation and image reconstruction. This advancement demonstrates the potential of neural operators in facilitating near real-time USCT reconstruction, making the clinical application of USCT increasingly viable and promising.

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@article{zeng2023neural,
  title  = {Neural Born Series Operator for Biomedical Ultrasound Computed Tomography},
  author = {Zhijun Zeng and Yihang Zheng and Youjia Zheng and Yubing Li and Zuoqiang Shi and He Sun},
  year   = {2023},
  eprint = {2312.15575},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2312.15575v1}
}

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