Fig. 3

A convolutional neural network (VNet architecture) was trained on arterial phase images of a dynamic contrast enhanced MRI dataset to automatically segment enhancing breast lesions. Two examples are shown (the worst and the best) with an average DICE coefficient of 0.82 ± 0.15. The pink color denotes the pixels that where considered from the network as a lesion while the white pixels where corresponding to the radiologists’ segmentation used as the ground truth. The DICE coefficient is defined as 2 * the Area of Overlap between the pink and white areas divided by the total number of pixels in the segmentation mask. 130 patients in total were recruited for the training of the model