Fig. 3: Box plot showing metric distributions assessing agreement between true and predicted tumour segmentations for test patients with invasive carcinoma of no special type. | npj Breast Cancer

Fig. 3: Box plot showing metric distributions assessing agreement between true and predicted tumour segmentations for test patients with invasive carcinoma of no special type.

From: Supporting intraoperative margin assessment using deep learning for automatic tumour segmentation in breast lumpectomy micro-PET-CT

Fig. 3

The following metrics are shown: the dice similarity coefficient (DSC), the area under the curve of the precision-recall curve (PR-AUC), the 95th percentile of the Hausdorff distance (95HD) in mm, and the contour dice with a 1 mm tolerance (1mmCD). The metrics are shown per model input (micro-CT, micro-PET, or micro-PET-CT) and per segmentation strategy (Intensity thresholding, or Residual U-Net (ResU-Net)).

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