Contrast-enhanced ultrasonography parameters in neural network diagnosis of liver tumors

Figure 2 Graphical representation of an artificial neural networks and a neuron from the 2nd hidden layer. A: The four classes of parameters are imputed to corresponding neurons in the first layer of the artificial neural networks, which in turn establish synaptic connections with all neurons of the 2nd hidden layer. These neurons provide a value for the output layer, which in turn presents the user with a classification decision; B: Neurons in the hidden layer receive multiple inputs (V) which are attributed specific weights (W) and all products between these two values are summed. The corresponding result (output) is forwarded through a transfer function of the efferent synapse. Imax: Maximum intensities; TTP: Time to reaching peak intensities.