Researchers at Oxford University Propose a Machine Learning Framework Called ‘TriSegNet’ Based on Triple-View Feature Learning for Medical Image Segmentation

Deep learning’s potential performance for medical imaging depends not only on the design of the network architecture but also on the availability of a sufficient amount of high-quality, manually annotated data, which is difficult to come by. Two techniques for semi-supervised learning that have received much attention are co-training and self-training. A model is initially […]

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