trondhauklien / bionano-project

bionano-project

Repository for source code used to analyse the particle tracking data recorded in the first part of the bionano project.

Image pre-processing with ImageJ

Videos from the microscope are processed using ImageJ using these simple steps:

1. Adjust auto contrast/brightness
2. Create Z-projection stack from average pixel values
3. Subtract the average image from all frames in the video, yelding a black backdrop with clearly visible particles.
4. Adjust auto contrast/brightness Export the video as an image sequence of .tif files, the data format which was most stable during TrackPy batch processing.

Record the pixel per micron value to the metadata.yml file by using the line tool (draw a line between the grids) and choose "Analyze > Set Scale...".

Particle tracking

Create an conda environment using the environment.yml file:

conda env create -f environment.yml

Run the tracking.py file for each image sequence. Update the hardcoded path to where the frames are stored. Rembember to adjust the parameters in the tp.batch() command such as diameter and minmass to remove any spurious particles.

Data processing

Use the notebook to process the data.

The tp.emsd() utility function does not work because it uses some deprecated Pandas function. This can be solved by downgrading Pandas, change the motion.py file in TrackPy or by soft-matter actually merging the pull request solving this issue.