Metadata-Version: 2.1
Name: SegmentationEvaluationTools
Version: 0.0.9
Summary: Tools for evaluating predictions on Simple-ITK Images
Home-page: https://github.com/brianmanderson/Segmentation_Evaluation_Tools
Author: Brian Mark Anderson
Author-email: bmanderson@mdanderson.org
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Description-Content-Type: text/markdown
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: SimpleITK
Requires-Dist: check-manifest

# Segmentation_Evaluation_Tools
There are a set of tools for creating quantitative comparison metrics based on ground truth and prediction SITK Image handles

## Installation
    pip install SegmentationEvaluationTools

### Usage
    from SegmentationEvaluationTools.SIKOverlapTools import calculate_overlap_measures, determine_sensitivity, 
    determine_false_positive_rate_and_false_volume, sitk

    truth_handle_base = sitk.ReadImage(image_path)
    prediction_handle_base = sitk.ReadImage(prediction_path)

    overlap_measures = calculate_overlap_measures(prediction_handle_base, truth_handle_base, measure_as_multiple_sites=False, perform_distance_measures=False)

    fp_measures = determine_false_positive_rate_and_false_volume(prediction_handle_base, truth_handle_base)

    sensitivity_measures = deteremine_sensitivity(prediction_handle=prediction_handle_base, truth_handle_base)


