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A network score-based metric to optimize the quality assurance of automatic target segmentation

This repository contains the code for the paper "A network score-based metric to optimize the quality assurance of automatic target segmentation", currently under review.

Reproducing results of the article

You can reproduce the results of the article with the script his_main.py

  • To get the score-based metrics, run cell 1.
  • To get the correlation results from Tables 3 and S3, run cell 2.
  • To plot figure 2, run cell 3.
  • To get the AUC curves, run cell 4.
  • To get scatter plots, run cell 5.

Information about trained models

The nnU-Net was used as segmentation framework for this project (https://github.com/MIC-DKFZ/nnUNet). The trained models and JSON files related to its training are stored in the folder "training details".

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