README.md

ukbb_lax_4ch_segmentation

Segmenting long-axis 4-chamber view Cardiac MRI with a U-Net deep convolutional neural network model and measure the dimensions of the 4 chambers.

Set up the python environment (installing all python package dependencies)

To ensure all required packages are installed, run the following command:

pip install -r requirements.txt

Package List:

backcall==0.2.0
certifi==2021.10.8
charset-normalizer==2.0.7
cycler==0.11.0
decorator==4.4.2
idna==3.3
imageio==2.10.4
kiwisolver==1.3.2
matplotlib==3.4.3
networkx==2.6.3
numpy==1.21.4
opencv-contrib-python-headless==4.5.4.58
pandas==1.3.4
Pillow==8.4.0
pydicom==2.2.2
pyparsing==3.0.6
python-dateutil==2.8.1
pytz==2021.3
PyWavelets==1.2.0
pyzmq==20.0.0
requests==2.26.0
scikit-image==0.18.3
scipy==1.7.2
six==1.15.0
tifffile==2021.11.2
torch==1.10.0
torchvision==0.11.1
tqdm==4.62.3
typing-extensions==3.10.0.2
urllib3==1.26.7

Setup: download the test data and the model weights

Run the download.py file, use the following command.

python download.py

Running the code with a tutorial

To see the process with a step by step illustration, open the Tutorial.ipynb notebook with a jupyter server.

Use the measurement python script

Run the file measurements/measure_4ch.py with default arguments will generate the measurements on the test data.

python measurements/measure_4ch.py

Run the file measurements/measure_4ch.py with arguments --save_fig and --csv test_data/labels_savefig.csv will generate the measuring figures on the test data.

python measurements/measure_4ch.py --csv test_data/labels_savefig.csv --savefig

Results

The segmentation of the examples would be like the images shown below:

Example 1:

Example 2:

Example 3: