Figure 6. Intermediate steps in the generative process.

(a) Randomly sampled input label map from the training set. (b) Spatially augmented input label map; imperfect 3D reconstruction is simulated with a deformation jitter across the coronal plane. (c) Synthetic image obtained by sampling from a Gaussian mixture model conditioned on the segmentation, with randomized means and variances. (d) Slice spacing is simulated by downsampling to low resolution. This imaging volume is further augmented with a bias field and intensity transforms (brightness, contrast, gamma). (e) The final training image is obtained by resampling (d) to high resolution. The neural network is trained with pairs of images like (e) (input) and (b) (target).