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Enhancing Retinal Blood Vessel Segmentation through Self-Supervised Pre-Training
2020
Proceedings (MDPI)
The segmentation of the retinal vasculature is fundamental in the study of many diseases. However, its manual completion is problematic, which motivates the research on automatic methods. Nowadays, these methods usually employ Fully Convolutional Networks (FCNs), whose success is highly conditioned by the network architecture and the availability of many annotated data, something infrequent in medicine. In this work, we present a novel application of self-supervised multimodal pre-training to
doi:10.3390/proceedings2020054044
fatcat:crkjipbjcfe33cmg6y3jcqzrmy