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This paper discusses the deep learning architectures currently used for pixel-wise segmentation of primary and secondary glioblastomas and low-grade gliomas. We implement various models such as the popular UNet architecture and compare the performanc
Externí odkaz:
http://arxiv.org/abs/1806.03981