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MyoBand

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

Simulation

Run python3 simulation.py to simulate A bands.

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Analysis

Get the skeletons of the A bands by running python3 get_skeletons.py -d DATA_LOCATION

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Installation

  • Install with pip install myoband
  • Clone this repo in order to use examples

Details

  • 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 using myoband.plotting.imshow(example_slide).
  • Gaussian noise can be added and removed (see skeleton_example.py, in which the robustness of the programme is benchmarked).

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  • Contours of the A bands can be extracted. This feature is used to extract the separate A bands from the image slide.

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  • Run get_skeletons.py to extract (a) a mask representation of the skeletons and (b) a list of points of the skeletons.

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Copyright, 23 March 2023, Henry Joseph Sheehy. All rights reserved.

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Myofibril A band simulation and analysis

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