Fluorescence pharmacokinetic parametric imaging method based on dynamic diffuse fluorescence tomography and deep learning

Yanqi Zhang; Limin Zhang; Han Liu; Ping Wang; Ailin Hou; Guohe Wang; Shaokai Sun

doi:10.1117/12.2637777

19 December 2022 Fluorescence pharmacokinetic parametric imaging method based on dynamic diffuse fluorescence tomography and deep learning

Yanqi Zhang, Limin Zhang, Han Liu, Ping Wang, Ailin Hou, Guohe Wang, Shaokai Sun

Author Affiliations +

Proceedings Volume 12320, Optics in Health Care and Biomedical Optics XII; 123201M (2022) https://doi.org/10.1117/12.2637777
Event: SPIE/COS Photonics Asia, 2022, Online Only

Conference Poster

Abstract

At present, the imaging of fluorescence pharmacokinetic parameters based on dynamic diffuse fluorescence tomography (D-DFT) technology have limitations in some aspects including the accuracy of physical model and the quantification of method. In this work, we propose a fluorescence pharmacokinetic parametric imaging method of tumor tissues based on D-DFT and deep learning. It mainly includes: a more realistic training and test simulation data set can be established by combining non-uniform tissue photon transport model and biological tissue fluorescence kinetics method. A fluorescence pharmacokinetic parametric reconstruction algorithm that involves an improved U-Net architecture based on the fully convolutional neural network is developed to break through the complexity bottleneck of imaging physical model. The numerical simulation results show that the method can realize image reconstruction of pharmacokinetic parameters with high spatial resolution and high quantitative accuracy.

Citation Download Citation

Yanqi Zhang, Limin Zhang, Han Liu, Ping Wang, Ailin Hou, Guohe Wang, and Shaokai Sun "Fluorescence pharmacokinetic parametric imaging method based on dynamic diffuse fluorescence tomography and deep learning", Proc. SPIE 12320, Optics in Health Care and Biomedical Optics XII, 123201M (19 December 2022); https://doi.org/10.1117/12.2637777

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