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Commit 5ff4fd6c authored by Laurent Guerard's avatar Laurent Guerard
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Update README adding links and replacing Weka by Cellpose

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......@@ -9,22 +9,22 @@ Original publication: <https://doi.org/10.1371/journal.pone.0229041>
Original code: <https://github.com/Hyojung-Choo/Myosoft/tree/Myosoft-hub>
## `1_identify_fibers.py`
## [`1_identify_fibers.py`](1_identify_fibers.py)
- Will identify all fibers based on the membrane staining using WEKA pixel
classification, filter them according to the morphometric gates and save the
- Will identify all fibers based on the membrane staining using [Cellpose](https://github.com/MouseLand/cellpose) segmentation, filter them according to the morphometric gates and save the
corresponding ROIs.
- Will now also save the WEKA segmentation as a binary so it can be edited
- Need to be installed ont the machine where the script is run. Follow [this guide](https://wiki.biozentrum.unibas.ch/display/IMCF/Cellpose+python+environment) to create the environment.
- Will now also save the Cellpose segmentation as a binary so it can be edited
manually. If you do so, you need to run the "extended particle analyzer"
manually as well to choose & apply the morphometric gates.
- Can be run in batch.
## `2a_identify_MHC_positive_fibers.py`
## [`2a_identify_MHC_positive_fibers.py`](2a_identify_MHC_positive_fibers.py)
- Allows to manual re-run the MHC positive fiber detection. Useful in case you
would like to re-run detection with a manual threshold for an image.
## `2b_central_nuclei_counter.py`
## [`2b_central_nuclei_counter.py`](2b_central_nuclei_counter.py)
- Will identify centralized nuclei given a ROI-zip together with its
corresponding image.
......@@ -32,14 +32,14 @@ Original code: <https://github.com/Hyojung-Choo/Myosoft/tree/Myosoft-hub>
information of a MHC staining channel.
- The ROI color code is annotated in the results table.
## `2c_fibertyping.py`
## [`2c_fibertyping.py`](2c_fibertyping.py)
- Identifies positive fibers in up to 3 channels given a ROI-zip together with
its corresponding image.
- Includes identification of double and triple positive combinations.
- The ROI color code is annotated in the results table.
## `3_manual_rerun.py`
## [`3_manual_rerun.py`](3_manual_rerun.py)
- Requires an already open image with an already populated ROI manager.
- Allows to manually select measurement parameters and the measurement channel.
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