Repository for code from the paper "Efficient model monitoring for quality control in cardiac image segmentation".

It contains all the scripts and utility programs for implementing our framework.

Authors: Francesco Galati and Maria A. Zuluaga.

• PyTorch 1.6.0
• CUDA 10.1 (to allow use of GPU, not compulsory)
• nibabel
• medpy

All the python classes and functions strictly needed to implement the framework can be found in CA.py.

We demonstrate its effectiveness by reproducing the results of the ACDC Challenge in QC.ipynb, in the absence of ground truth. Inside the notebook you can also find an automatic procedure to tune hyperparameters in case ours do not adapt to your data.

If you use this software, please cite the following paper as appropriate:

Galati, F., Zuluaga, M. A. (2021).
Efficient model monitoring for quality control in cardiac image segmentation.
In: 11th Biennal Conference on Functional Imaging and Modeling of the Heart (FIMH)
https://arxiv.org/abs/2104.05533

Copyright 2020.

This software is released under the BSD-3 license. Please see the license file_ for details.