Figure 3.

A representation of the basic architecture of an unsupervised neural network.

First, feature maps are made from MRI, CT, or PET images. Next, pooling layers summarize the feature maps. This step is repeated through multiple neural layers. Then, the final feature maps are sent to the final fully connected layer, where predictions and masks are made, leading to the eventual model output. Adapted from Gautam and Sharma (2020).