Neural Born Series Operator for Biomedical Ultrasound Computed
  Tomography
Zhijun Zeng Yihang Zheng Youjia Zheng Yubing Li Zuoqiang Shi He Sun
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.