Deep learning based depth map estimation of
protoporphyrin IX in turbid media using dual
wavelength excitation fluorescence
Posted on 2023-09-18 - 16:11
This study presents a depth map estimation of fluorescent objects in turbid media, such as biological tissue based on fluorescence observation by two-wavelength excitation and deep learning-based processing. A U-Net-based convolutional neural network is adapted for fluorophore depth maps from the ratiometric information of the two-wavelength excitation fluorescence. The proposed method offers depth map estimation from wide-field fluorescence images with rapid processing. The feasibility of the proposed method was demonstrated experimentally by estimating the depth map of protoporphyrin IX, a recognized cancer biomarker, at different depths within an optical phantom.
CITE THIS COLLECTION
Imanishi, Hinano; Nishimura, Takahiro; Shimojo, Yu; Awazu, Kunio (2023). Deep learning based depth map estimation of protoporphyrin IX in turbid media using dual wavelength excitation fluorescence. Optica Publishing Group. Collection. https://doi.org/10.6084/m9.figshare.c.6831408.v2
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