We extend the IoU calculation from 2D to 3D but in order to be simple, we only deal with 3D boxes / cubes. Although the detections we have are 3D spheres output from the grt123 system. The threshold we currently use is 0.5 but can easily be changed (‘correct_detection_threshold’ in evaluate_detection.py). We also did some experiments using different thresholds, please check the evaluation results below.
You can see we include a results file that can be compared with the ground truth file in
concept-to-clinic/prediction/src/algorithms/training/detector/label/custom_annos.csv
Screenshots (if appropriate):
CLA
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lamby
commented
6 years ago
Description
Correct detection A detection can be treated as a correct detection if the intersection-over-union (IoU) of the ground truth and the detected bounding boxes is larger than a predefined threshold. The concept is shown as below. (Images are borrowed from https://www.pyimagesearch.com/2016/11/07/intersection-over-union-iou-for-object-detection/)
Reference to official issue
Issue #271
Motivation and Context
How Has This Been Tested?
We have tested the performance on the NSCLC Radiogenomics data set found here: http://www.cibl-harvard.org/data
You can see we include a results file that can be compared with the ground truth file in concept-to-clinic/prediction/src/algorithms/training/detector/label/custom_annos.csv
Screenshots (if appropriate):
CLA