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. 2023 Dec 28:9:1275.
doi: 10.12688/f1000research.27158.3. eCollection 2020.

DeepCLEM: automated registration for correlative light and electron microscopy using deep learning

Rick Seifert  1   2 , Sebastian M Markert  2 , Sebastian Britz  2 , Veronika Perschin  2 , Christoph Erbacher  3 , Christian Stigloher  2 , Philip Kollmannsberger  1
Affiliations

DeepCLEM: automated registration for correlative light and electron microscopy using deep learning

Rick Seifert et al. F1000Res. .

Abstract

In correlative light and electron microscopy (CLEM), the fluorescent images must be registered to the EM images with high precision. Due to the different contrast of EM and fluorescence images, automated correlation-based alignment is not directly possible, and registration is often done by hand using a fluorescent stain, or semi-automatically with fiducial markers. We introduce "DeepCLEM", a fully automated CLEM registration workflow. A convolutional neural network predicts the fluorescent signal from the EM images, which is then automatically registered to the experimentally measured chromatin signal from the sample using correlation-based alignment. The complete workflow is available as a Fiji plugin and could in principle be adapted for other imaging modalities as well as for 3D stacks.

Keywords: Correlative Microscopy; Deep Learning; Image Registration; In-silico labeling.

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Conflict of interest statement

No competing interests were disclosed.

Figures

Figure 1.
Figure 1.. Schematic of the "DeepCLEM" workflow.
From the EM image ( A), a CNN predicts the chromatin channel ( B), to which the SIM image ( C) is registered ( D). The same transform is applied to the channel of interest ( E) to obtain a CLEM overlay ( F).
Figure 2.
Figure 2.. GUI and input parameters for "DeepCLEM".
See this image and copyright information in PMC

References

    1. Markert SM, Britz S, Proppert S, et al. : Filling the gap: adding super-resolution to array tomography for correlated ultrastructural and molecular identification of electrical synapses at the C. elegans connectome. Neurophotonics. 2016;3(4): 041802. 10.1117/1.NPh.3.4.041802 - DOI - PMC - PubMed
    1. Markert SM, Bauer V, Muenz TS, et al. : 3D subcellular localization with superresolution array tomography on ultrathin sections of various species. Methods Cell Biol. 2017;140:21–47. 10.1016/bs.mcb.2017.03.004 - DOI - PubMed
    1. García-Fernández E, Koch G, Wagner RM, et al. : Membrane Microdomain Disassembly Inhibits MRSA Antibiotic Resistance. Cell. 2017;171(6):1354–1367. e20. 10.1016/j.cell.2017.10.012 - DOI - PMC - PubMed
    1. Cardona A, Saalfeld S, Schindelin J, et al. : TrakEM2 Software for Neural Circuit Reconstruction. PLoS One. 2012;7(6): e38011. 10.1371/journal.pone.0038011 - DOI - PMC - PubMed
    1. Paul-Gilloteaux P, Heiligenstein X, Belle M, et al. : eC-CLEM: flexible multidimensional registration software for correlative microscopies. Nat Methods. 2017;14(2):102–103. 10.1038/nmeth.4170 - DOI - PubMed

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