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Neural Born Series Operator for Biomedical Ultrasound Computed Tomography

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arxiv 2312.15575 v2 pith:EANLXV6C submitted 2023-12-25 eess.IV cs.CVcs.LG

Zhijun Zeng , Yihang Zheng , Youjia Zheng , Yubing Li , Zuoqiang Shi , He Sun This is my paper · ORCID
classification eess.IVcs.CVcs.LG
keywords usctreconstructionclinicalneuralborncomputedefficientfacilitating
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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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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. OpenBreastUS: Benchmarking Neural Operators for Wave Imaging Using Breast Ultrasound Computed Tomography

    cs.CV 2025-07 conditional novelty 6.0 of 10

    OpenBreastUS provides a large-scale, anatomically realistic benchmark of 16 million breast ultrasound simulations and demonstrates neural-operator-based full-waveform inversion on clinical in vivo breast data.

  2. Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning

    cs.LG 2025-06 conditional novelty 4.0 of 10

    A practical recipe to convert common neural architectures into discretization-agnostic neural operators, validated by Navier-Stokes experiments showing cross-resolution generalization of FNO-style models.

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