Fig. 1
From: Automatic segmentation of head and neck primary tumors on MRI using a multi-view CNN
The MV-CNN architecture used in the current study. On the left side, the schematic overview with the pyramid structure (scale 0 and scale 1). Each branch of the MV-CNN has the same structure, which is shown on the right, consisting of convolutional (with batch normalization (BN) and ReLu activation), max pooling, dropout and dense layers. The outputs of the branches are concatenated and with two dense layers reduces to the output of size two, representing non-tumor and tumor