Skip to content

1-class and 2-class segmentation of axon/myelin using nnunetv2

Notifications You must be signed in to change notification settings

axondeepseg/nn-axondeepseg

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

24 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Warning

This repository is no longer maintained. Please install AxonDeepSeg v5 or higher instead.

nnAxonDeepSeg

1-class and 2-class segmentation of axon/myelin using nnunetv2

Usage

First create a virtual environment (using pipenv, conda, etc.). Note that this project requires a python version >= 3.9 Then, install the requirements:

pip install -r requirements.txt

The inference tool should now be ready to use. First, download a model using the following command. The user will be prompted to specify which model to download.

python download_models.py

Then, you can use the nn_axondeepseg.py script to apply the model to your images. Assuming the images are in a folder called input, you can use

python nn_axondeepseg.py --seg-type UM --path-out output-folder --path-dataset input

The --seg-type argument is used to specify which kind of model is used: UM stands for unmyelinated axon, for which we expect a single class output; AM stands for axon and myelin, for which we expect a 2-class output. The user can specify any nnUNet model using the --path-model argument.

About

1-class and 2-class segmentation of axon/myelin using nnunetv2

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages