BNCNN based diffuse optical imaging

Nazish Murad, Min Chun Pan, Ya Fen Hsu

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

We proposed and implemented a deep learning scheme using convolution neural networks (CNNs) with batch normalization (BNCNN) to construct a sensor-image DOI computation model with the aim of reconstructing tissue optical-property images as well as identifying and localizing breast tumors. A non-iterative learning reconstruction method was developed to recover optical properties, focusing on one-dimensional convolution layers followed by dense layers. Besides simulated data for model training, validation and testing, for the comparison of model performance, measurement data sets were employed to test on the same trained network which results outperform Tikhonov regularization method and other artificial neural networks as well.

原文???core.languages.en_GB???
主出版物標題Multimodal Biomedical Imaging XVII
編輯Fred S. Azar, Xavier Intes, Qianqian Fang
發行者SPIE
ISBN(電子)9781510647756
DOIs
出版狀態已出版 - 2022
事件Multimodal Biomedical Imaging XVII 2022 - San Francisco, United States
持續時間: 22 1月 202227 1月 2022

出版系列

名字Progress in Biomedical Optics and Imaging - Proceedings of SPIE
11952
ISSN(列印)1605-7422

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???event.eventtypes.event.conference???Multimodal Biomedical Imaging XVII 2022
國家/地區United States
城市San Francisco
期間22/01/2227/01/22

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