Neural Born Series Operator for Biomedical Ultrasound Computed Tomography

Autor:	Zeng, Zhijun, Zheng, Yihang, Zheng, Youjia, Li, Yubing, Shi, Zuoqiang, Sun, He
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing Computer Science - Computer Vision and Pattern Recognition Computer Science - Machine Learning I.4.5 J.3
Druh dokumentu:	Working Paper
Popis:	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.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2312.15575 Zobrazit plný text záznamu View this record from Arxiv