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metrics for evaluating lesion segmentations

Project description

lesion-metrics

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metrics for evaluating lesion segmentations

Install

The easiest way to install the package is with:

pip install lesion-metrics

Alternatively, you can 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 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

0.1.0 (2021-05-14)

  • First release on PyPI.

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