The ROIs are calculated for a given interval of frames. By default, a single ROI is calculated for groups of 10 frames to speed up the process based on the fact that the sample signal won't change considerably within this interval. This is a good approximation and the speed up justifies the eventual errors in readings caused by movement (see activity.ipynb for details about the error in activity caused by downsampling).
The ROI algorithm can be resumed as:
- Average the group of frames into a single 2D matrix
- Automatic threshold (Otsu's method)
- Binarize the image
- Remove small holes inside the VNC
- Select the largest group of connected foreground pixels
- Return a mask that matches the largest label
To calculate the signal intensity, we apply the mask to the embryo and calculate the mean pixel value.
The active and structural channel measurements are exported as a .csv file and further processed using the code from snazzy_analysis.
The ROIs can be inspected visually by running the plot_countours.py script.
The script displays a matplotlib animation with an overlayed ROI contour.
To display it, cd into the snazzy_processing directory, and run the file:
python3 scripts/plot_contours.pyIt will look for any experiment directories you have inside the ./data directory and present the available options in the terminal.
Animations can be paused by pressing any key.