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Unlocking the Heart Using Adaptive Locked Agnostic Networks
Supervised training of deep learning models for medical imaging applications requires a significant amount of labeled data.
Whole-brain substitute CT generation using Markov random field mixture models
The amount of data needed to train a model for s-CT generation is of the order of 100 million voxels.
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