Fig. 1From: Convolutional neural network -based phantom image scoring for mammography quality controlPre-processing a phantom image (A) consisted of cropping and rotation of the wax area (B) and replacing the phantom name and corners with noise (C). Each fibre, mass, and microcalcification group was then separated into an individual sub-image (D)Back to article page