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Project work (group 1) from Defragmentation Workshop from October 2022

Group members:

  • Daniel Waiger
  • Camille Loiseau
  • Tatiana Woller
  • Anna Agafonova
  • Gayathri Nadar

This project would not have been successful without the friendly collaboration of the team members :)

Analysis Goal

  • Segment 'only' the cytoplasm (neurons) in confocal single slice mouse brain images with no nuclei stain.

Workflow

  1. save_tiff.py: save the images saved in propietary format into tiff for easy accessibility by other programs. The channels are split and saved separately. Works on a folder of images.
  2. cytoplasm_segmentation.ipynb:
    • Read images in folder, randomly pick one for training an Object classifier in napari-devbio package.
    • Initially training could be done by adding labels in napari window.
    • Option to also load labels from image file - possibly saved using napari > labels > save as image.
    • We train a classifier to identify cytoplasm region in cells.
    • The classifier is saved to disk.
  3. batch_prediction_using_classifier.ipynb:
    • Read images in folder, read classifier model
    • Apply to images in the folder in a loop and save label maps of the segmentation.

Images

  • Images used for training: 2D, single channel containing the cytoplasm