metrics for evaluating lesion segmentations
Project description
lesion-metrics
Various metrics for evaluating lesion segmentations [1]
Free software: Apache Software License 2.0
Documentation: https://lesion-metrics.readthedocs.io.
Install
The easiest way to install the package is with:
pip install lesion-metrics
To install the dependencies of the CLI, install with:
pip install "lesion-metrics[cli]"
You can also download the source and run:
python setup.py install
Basic Usage
You can generate a report of lesion metrics for a directory of predicted labels and truth labels with the CLI:
lesion-metrics -p predictions/ -t truth/ -o output.csv
Or you can import the metrics and run them on label images:
import nibabel as nib
from lesion_metrics.metrics import dice
pred = nib.load('pred_label.nii.gz').get_fdata()
truth = nib.load('truth_label.nii.gz').get_fdata()
dice_score = dice(pred, truth)
References
[1] Carass, Aaron, et al. “Longitudinal multiple sclerosis lesion segmentation: resource and challenge.” NeuroImage 148 (2017): 77-102.
History
0.1.3 (2021-06-07)
Fix correlation computation in CLI and other minor typos.
0.1.2 (2021-05-26)
Update code style to black and improve docs.
0.1.1 (2021-05-14)
Fix repo name.
0.1.0 (2021-05-14)
First release on PyPI.
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