A Deep Learning Method to Process Scattered Field Data in Biomedical Imaging System

Journal of Beijing Institute of Technology ›› 2024, Vol. 33 ›› Issue (3) : 213 -218.

PDF (4654KB)
Journal of Beijing Institute of Technology ›› 2024, Vol. 33 ›› Issue (3) : 213 -218. DOI: 10.15918/j.jbit1004-0579.2024.028

A Deep Learning Method to Process Scattered Field Data in Biomedical Imaging System

Author information +
History +
PDF (4654KB)

Abstract

This paper proposed a deep-learning-based method to process the scattered field data of transmitting antenna, which is unmeasurable in inverse scattering system because the transmitting and receiving antennas are multiplexed. A U-net convolutional neural network (CNN) is used to recover the scattered field data of each transmitting antenna. The numerical results proved that the proposed method can complete the scattered field data at the transmitting antenna which is unable to measure in the actual experiment and can also eliminate the reconstructed error caused by the loss of scattered field data.

Keywords

inverse problem / scattered field / deep learning

Cite this article

Download citation ▾
null. A Deep Learning Method to Process Scattered Field Data in Biomedical Imaging System. Journal of Beijing Institute of Technology, 2024, 33(3): 213-218 DOI:10.15918/j.jbit1004-0579.2024.028

登录浏览全文

4963

注册一个新账户 忘记密码

References

AI Summary AI Mindmap
PDF (4654KB)

437

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/