Fig. 4: Predicted tumour contours for two specimens with invasive carcinomas of no special type. | npj Breast Cancer

Fig. 4: Predicted tumour contours for two specimens with invasive carcinomas of no special type.

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

Fig. 4

For every specimen, three orthogonal slices are visualised. The top row shows the micro-PET-CT input, and the bottom row shows the contours on top of the micro-CT. The micro-PET and micro-CT images are expressed in standardised uptake values (SUVs) and Hounsfield units (HUs), respectively. The specimen contour is shown in blue, and the contours of the tumour predictions are shown in orange and green for the Residual U-Net (ResU-Net) and intensity thresholding, respectively. a Specimen with negative histopathological margin. The ResU-Net prediction is true negative, while intensity thresholding leads to a false positive prediction. b Specimen with positive histopathological margin. Both ResU-Net and intensity thresholding predictions are true positive.

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