Segmentation of nuclei using DSB-2018 top-1 neural network model

Based on selimsef/dsb2018_topcoders

For comparison of Data Science Bowl 2018 best segmentation models see Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl, Juan C. Caicedo et al.

Installation

1. Clone this repository

git clone https://github.com/yozhikoff/segmentation.git

2. Download this and extract it to the segmentation folder, replace all existing files using Ay keys when unzip asks about it. Note that you need to export to /repo/segmentation/dsb2018_topcoders withing the repo.

wget https://www.dropbox.com/s/qvtgbz0bnskn9wu/dsb2018_topcoders.zip?dl=1 dsb2018_topcoders.zip # note dl=1
unzip /path/to/zip/dsb2018_topcoders.zip -d /path/to/repo/segmentation/dsb2018_topcoders #type "Ay" when it asks about conflicts

3. Go to the segmentation folder and reset git files

cd /path/to/repo/segmentation
git reset --hard

4. Create new conda env

conda create -n seg python=3.6.9 -y
conda activate seg

5. Install packages via conda and pip, simply (inside your conda env!)

sh ./install.sh

6. Test your installation using

python run_test.py

You can also try example_notebook.ipynb if you want to see usage details.