  We proposed a two stage framework with only one network to analyze skin
lesion images, we firstly trained a convolutional network to classify these
images, and cropped the import regions which the network has the maximum
activation value. In the second stage, we retrained this CNN with the image
regions extracted from stage one and output the final probabilities. The two
stage framework achieved a mean AUC of 0.857 in ISIC-2017 skin lesion
validation set and is 0.04 higher than that of the original inputs, 0.821.
