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Fig. 5

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ZDB-FIG-230327-40

Publication

Shin et al., 2022 - Three-dimensional fluorescence microscopy through virtual refocusing using a recursive light propagation network

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Fig. 5

Fig. 5. Virtual refocusing of C. elegans images. (a) Two adjacent images used as the input. Each region-of-interest shows head ganglia, body, and tail ganglia, respectively. (b) MIPs of the reconstructed volume using RLP-Net (left) and the ground-truth (right). In each panel, lateral ( $x y$ $x y$ ) MIP (top-left), axial ( $x z$ $x z$ ) MIP (bottom-left), and axial ( $y z$ $y z$ ) MIP (right) are shown. (c) The ground truth images (1st row) are compared with the refocusing results from Deep-Z (2nd row) and RLP-Net (3rd row). Different neurons are in focus at different axial locations. Scale bars, 20 $μ$ $μ$ m.

Expression Data

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Antibody Labeling

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Acknowledgments

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Reprinted from Medical image analysis, 82, Shin, C., Ryu, H., Cho, E.S., Han, S., Lee, K.H., Kim, C.H., Yoon, Y.G., Three-dimensional fluorescence microscopy through virtual refocusing using a recursive light propagation network, 102600, Copyright (2022) with permission from Elsevier. Full text @ Med. Image Anal.