In Frontiers in neuroscience
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).
Kuzina Anna, Egorov Evgenii, Burnaev Evgeny
3D CNN, Bayesian neural networks, brain lesion segmentation, brain tumor segmentation, transfer learning, variational autoencoder