Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems.
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ABSTRACT:
SUBMITTER: Kuzina A
PROVIDER: S-EPMC6712162 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Publications
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems.
Kuzina Anna A Egorov Evgenii E Burnaev Evgeny E
Frontiers in neuroscience 20190821
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 C ...[more]
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