Figure 2.

Illustration of single‐channel CNN and multichannel CNN. The single‐channel CNN in (a) computes the probability of assigning a specific tissue label to the center voxel of the input 3D patch. The single‐channel CNN consists of three convolutional layers, one pooling layer, and one fully connected layer. The numbers of the filters, as well as the support of each filter, are marked on the top of each layer. In (b), a multichannel CNN is derived from several single‐channel CNNs, to account for the multichannel input patches in our proposed framework. The multichannel information includes multiscale image patch from CT and the probability map patch derived from previous iteration. The probability map generated by other CNNs can be treated as an input to the multichannel CNN here, such that the segmentation of all ROIs can be solved jointly and iteratively. [Color figure can be viewed at wileyonlinelibrary.com]