Neural Born Series Operator for Biomedical Ultrasound Computed Tomography

التفاصيل البيبلوغرافية
العنوان: Neural Born Series Operator for Biomedical Ultrasound Computed Tomography
المؤلفون: Zeng, Zhijun, Zheng, Yihang, Zheng, Youjia, Li, Yubing, Shi, Zuoqiang, Sun, He
سنة النشر: 2023
المجموعة: Computer Science
مصطلحات موضوعية: 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
الوصف: 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.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2312.15575
رقم الأكسشن: edsarx.2312.15575
قاعدة البيانات: arXiv