Fig. 2. A three-dimensional (3D) convolutional neural network (CNN) for contrast-enhanced ultrasound (CEUS).

Using a 3D-CNN has the advantage of analyzing not only the spatial information of CEUS, but also the temporal information. In the 3D-CNN, multiple CEUS images arranged in temporal order form the input layer. In the 3D-CNN, a 3D kernel is applied. The kernel is not only applied to two-dimensional (2D) images as a 2D sliding convolution of a 2D-CNN, but also applied over consecutive images simultaneously in a 3D-CNN. As a result, the temporal correlation between each image could be captured by this 3D convolution.