Common use of Model architecture and training procedure Clause in Contracts

Model architecture and training procedure. We apply a two stage model. In particular we apply the candidate detector of Karssemeijer2 which gives about 15 candidates per image at a near 100% sensitivity. Around these locations, we extract patches and classify these as malignant/benign using a convolutional neural network (CNN) which we describe below. Prior to classification, all images were bilinearly resampled to a 200µm pixel spacing. This resolution is considered a good trade-off between accuracy, memory usage and speed for the detection of soft tissue lesions.