Depth estimation of protoporphyrin IX objects in turbid media considering the fluorescence intensity ratio between two wavelengths of light for application in invasion diagnosis of gastric cancer

Imanishi, Hinano; Nishimura, Takahiro; Awazu, Kunio

doi:10.1007/s10043-022-00747-y

Opt Rev

2022

DOI: 10.1007/s10043-022-00747-y

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Depth estimation of protoporphyrin IX objects in turbid media considering the fluorescence intensity ratio between two wavelengths of light for application in invasion diagnosis of gastric cancer

Hinano Imanishi

Takahiro Nishimura

Kunio Awazu

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2023

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Deep learning based depth map estimation of protoporphyrin IX in turbid media using dual wavelength excitation fluorescence

Imanishi,

Nishimura,

Shimojo

et al. 2023

Biomed. Opt. Express

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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.

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Deep learning based depth map estimation of protoporphyrin IX in turbid media using dual wavelength excitation fluorescence

Imanishi,

Nishimura,

Shimojo

et al. 2023

Biomed. Opt. Express

View full text Add to dashboard Cite

show abstract

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Depth estimation of protoporphyrin IX objects in turbid media considering the fluorescence intensity ratio between two wavelengths of light for application in invasion diagnosis of gastric cancer

Cited by 1 publication

References 20 publications

Deep learning based depth map estimation of protoporphyrin IX in turbid media using dual wavelength excitation fluorescence

Deep learning based depth map estimation of protoporphyrin IX in turbid media using dual wavelength excitation fluorescence

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