Skip to content
This repository has been archived by the owner on Nov 21, 2022. It is now read-only.
/ opt_flow_reg Public archive

Optical flow based registration for fluorescence microscopy images

License

Notifications You must be signed in to change notification settings

BayraktarLab/opt_flow_reg

Repository files navigation

DOI

Optical flow based registration for immunofluorescence images

These scripts perform fine registration using warping. A map for warping is calculated using Farneback optical flow algorithm, by OpenCV. Although images are MINMAX normalized during processing, optical flow algorithms expect images to have similar pixel intensities.

Currently does not support z-stacks.

Command line arguments

-i path to image stack

-c name of reference channel

-o output directory

-n multiprocessing: number of processes, default 1

####Optional

--tile_size size of a square tile, default 1000, which corresponds to 1000x1000px tile

--overlap overlap between tiles, default 100

--num_pyr_lvl number of pyramid levels. Default 3, 0 - will not use pyramids

--num_iter number of registration iterations per pyramid level. Default 3, cannot be less than 1

Example usage

python opt_flow_reg.py -i /path/to/iamge/stack/out.tif -c "DAPI" -o /path/to/output/dir/ -n 3

Dependencies

numpy tifffile opencv-contrib-python dask scikit-learn

About

Optical flow based registration for fluorescence microscopy images

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages