  Automatic segmentation methods based on deep learning have recently
demonstrated state-of-the-art performance, outperforming the ordinary methods.
Nevertheless, these methods are inapplicable for small datasets, which are very
common in medical problems. To this end, we propose a knowledge transfer method
between diseases via the Generative Bayesian Prior network. Our approach is
compared to a pre-train approach and random initialization and obtains the best
results in terms of Dice Similarity Coefficient metric for the small subsets of
the Brain Tumor Segmentation 2018 database (BRATS2018).
