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data_and_evaluation

Code for generating the dataset and evaluation metrics discussed in Confluent Vessel Trees with Accurate Bifurcations which will appear in CVPR2021. The implementation of the data generation was forked from https://github.com/midas-journal/midas-journal-794 and the original project description is at http://www.insight-journal.org/browse/publication/794.

Instructions for running the evaluation

Python enviroment and dependencies

The script is tested under python 3.5.2. To install the dependencies, run

pip install -r requirements.txt

How to use the code

To obtain the ROC and angular error curves, use the exmaple script eval.sh. The input will be the reconstructed tree in H5 format (Our reconstructed trees (corresponding to the green curve below) are provided here.) and groundtruth in XML format. The output will be the average measure over the 15 volumes and saved in a file named "***Average.csv". This file contains the following variables.

To generate the "On whole tree" ROC curve,

X-axis: 1 - PercentageOfPointsCloserThanRadius
Y-axis: PercentageOfPointsCloserThanRadiusOrig

To generate the "On branching points" ROC curve,

X-axis: 1 - PercentageOfBifurPointsCloserThanRadius
Y-axis: PercentageOfBifurPointsCloserThanRadiusOrig

To generate the angular error plot,

X-axis: ThresholdValue
Y-axis: averageAngleAtBifur

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Data generation and evaluation metrics (Confluent Vessel Trees with Accurate Bifurcations, CVPR2021)

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