abstract

Functional 2-photon microscopy is a key technology for imaging neuronal activity which can, however, contain non-rigid movement artifacts. Despite the established performance of variational optical flow (OF) estimation in different computer vision areas and the importance of movement correction for 2-photon applications, no OF-based method for 2-photon imaging is available. We developed the easy-to-use toolbox Flow-Registration that outperforms previous alignment tools and allows to align and reconstruct even low signal-to-noise 2-photon imaging data.

Video Results


Supplemental video 1 (drug injection sequence)




Supplemental video 2 (saline injection sequences)




Supplemental video 3 (layer23 - layer1 - layer5 - CaPKA)




Supplemental video 4 (Jupiter demo)




Code and Citation


Source

The Flow-Registration toolbox will be available for download from GitHub soon.

Paper

Our paper preprint is available on BioRxiv.


Please cite our work with:

P. Flotho, S. Nomura, B. Kuhn and D. J. Strauss, “Software for Non-Parametric Image Registration of 2-Photon Imaging Data,” bioRxiv, 2021.

@article{flotea2021c,
    author = {Flotho, P. and Nomura, S. and Kuhn, B. and Strauss, D. J.},
    title = {Software for Non-Parametric Image Registration of 2-Photon Imaging Data},
	elocation-id = {2021.07.25.453381},
	year = {2021},
	doi = {10.1101/2021.07.25.453381},
    publisher = {Cold Spring Harbor Laboratory},
    journal = {bioRxiv}
}