Convolutional Neural Networks for the Segmentation of Microcalcification in Mammography Imaging

Figure 6

Example of segmentator failure case. The patch on the left represents the misclassified input sample containing a microcalcification, while the patch on the right is the (well classified) closest class C2 sample in the features space. Below, you can see the ground truth segmentations. Please note that the maximum possible error is equal to 1 and an error <0.5 means that the input patch is still correctly classified (best viewed in color).