Simulation and analysis of A bands in myofibril imaging
written in Python
.
Note: if the text in the images is unreadable due to dark mode, please open them in a new tab.
MyoBand in the Python repository
Run python3 simulation.py
to simulate A bands.
Get the skeletons of the A bands by running python3 get_skeletons.py -d DATA_LOCATION
- Install with
pip install myoband
- Clone this repo in order to use examples
- For A band creation see
A_band.py
in tests folder. - An A band is created by adding thickness to
a polynomial. The polynomial is created
using a random walk (see
randomwalk.py
). - A Slide is a 2D array of zeros.
A_Bands
are then added, forming a mask array. The slide can be viewed usingmyoband.plotting.imshow(example_slide)
. - Gaussian noise can be added and removed (see
skeleton_example.py
, in which the robustness of the programme is benchmarked).
- Contours of the A bands can be extracted. This feature is used to extract the separate A bands from the image slide.
- Run
get_skeletons.py
to extract (a) a mask representation of the skeletons and (b) a list of points of the skeletons.
Copyright, 23 March 2023, Henry Joseph Sheehy. All rights reserved.