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Found 2 papers, 1 papers with code
Influence of Early through Late Fusion on Pancreas Segmentation from Imperfectly Registered Multimodal MRI
We trained a collection of basic UNets with different fusion points, spanning from early to late, to assess how early through late fusion influenced segmentation performance on imperfectly aligned images.
An untrained deep learning method for reconstructing dynamic magnetic resonance images from accelerated model-based data
We conclude that the use of an untrained neural network together with a physics-based regularization loss shows promise as a measure for determining the optimal stopping point in training without relying on fully-sampled ground truth data.
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