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Segment axon and myelin from microscopy data using deep learning. Written in Python. Using the TensorFlow framework. Based on a convolutional neural network architecture. Pixels are classified as either axon, myelin or background.

For more information, see the documentation website.

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  • If you encounter difficulties during installation and/or while using AxonDeepSeg, or have general questions about the project, you can start a new discussion on the AxonDeepSeg GitHub Discussions forum. We also encourage you, once you've familiarized yourself with the software, to continue participating in the forum by helping answer future questions from fellow users!
  • If you encounter bugs during installation and/or use of AxonDeepSeg, you can open a new issue ticket on the AxonDeepSeg GitHub issues webpage.

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AxonDeepSeg

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Citation

If you use this work in your research, please cite it as follows:

Zaimi, A., Wabartha, M., Herman, V., Antonsanti, P.-L., Perone, C. S., & Cohen-Adad, J. (2018). AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks. Scientific Reports, 8(1), 3816. Link to paper: https://doi.org/10.1038/s41598-018-22181-4.

Copyright (c) 2018 NeuroPoly (Polytechnique Montreal)

Licence

The MIT License (MIT)

Copyright (c) 2018 NeuroPoly, École Polytechnique, Université de Montréal

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Contributors

Pierre-Louis Antonsanti, Stoyan Asenov, Mathieu Boudreau, Oumayma Bounou, Marie-Hélène Bourget, Julien Cohen-Adad, Victor Herman, Melanie Lubrano, Antoine Moevus, Christian Perone, Vasudev Sharma, Thibault Tabarin, Maxime Wabartha, Aldo Zaimi.

ometiff-tests's People

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ometiff-tests's Issues

Test file conversions with notebook

I tested the notebook on Ubuntu 20.04 in WSL 1:

I have a few questions/observations about the tests.

1) Read OME-TIFF image + metadata:

  • I got this message when running the cell: OME series: failed to read 'tubhiswt_C1.ome.tif', which is normal because the file C1 is not in the repo.
  • However, in the displayed metadata, there is some metadata for C1, ex: {'UUID': {'FileName': 'tubhiswt_C1.ome.tif', 'value': 'urn:uuid:f801ea0a-e93e-4f4f-99b3-7ecc15048c12'}, 'FirstC': 1, 'FirstT': 2, 'FirstZ': 0, 'IFD': 2, 'PlaneCount': 1}
  • And the display of "timepoints" gives me the following image, with the second row being empty:
    tubhiswt_timepoints
  • It looks like the 2 files are "linked" somehow through metadata in OMETIFF? (I suspect Etienne had the two files on his drive, but only 1 is in the repo). If that is the case, this is an OMETIFF feature that I was not aware of...

Write OME-TIFF image + metadata:

  • If I understand correctly, I think the file should have 10 "timepoints" and 3 "channels". However, when I read the OMETIFF file written by tifffile in Fiji/Bioformats, I get an image and metadata with 30 "timepoints" (SizeT = 30) and 1 "channel" (SizeC = 1).
  • Also, we should document what compress=7 means in the call of tifffile.imwrite.

3.1) TIFF to OME-TIFF:

  • Why do we need to add an alpha channel? This should be documented.
  • When I read the OMETIFF file written by pyvids in Fiji/Bioformats, I got the right dimension in metadata but the image is a repetition of a tiles?
    tof_to_ometiff
  • There is also a warning in the console, I don't know if it's related:
[WARN] SamplesPerPixel mismatch: OME=-1, TIFF=1
[WARN] Image ID 'Image:0': missing plane #0
[WARN] Using TiffReader to determine the number of planes.

3.2.2) Generate the OMETIFF with the NDPI data:

  • For some unknown reason, when I open the generated OMETIFF file in Fiji/Bioformats, the image on the 3 channels appears totally black, although the validation at point 3.2.3 shows the correct image. I updated the Bioformats version to the latest i.e. 6.6.1.

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