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Strategies for Training Deep Learning Models in Medical Domains with Small Reference Datasets
2020
Journal of WSCG
With the steady progress of Deep Learning (DL), powerful tools are now present for sophisticated segmentation tasks. Nevertheless, the generally very high demand for training data and precise reference segmentations often cannot be met in medical domains when processing small and individual studies or acquisition protocols. As common strategies, reinforcement learning or transfer learning are applicable but coherent with immense effort due to domain-specific adjustment. In this work the
doi:10.24132/jwscg.2020.28.5
fatcat:jle43tluxzflri5wnlgt54yska