Figure 2.

Simplified architecture of a convolutional neural network (CNN). Images acquired with digital pathology are composed of pixels. The color of each pixel can be represented with values of the red, green and blue (RGB) scheme. RGB arrays are subjected to filters to create a convolutional layer. Filters detect specific features from an image (e.g., lines, edges). A pooling layer with a reduced number of parameters is created by summarizing (subsampling) the input of the convolutional layer. After a defined number of convolutional and pooling layers, fully connected layers are created. Fully connected layers are uni-dimensional layers from which the output is predicted.