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Found 4 papers, 0 papers with code
Learning Task-Specific Strategies for Accelerated MRI
Traditional CS-MRI methods often separately address measurement subsampling, image reconstruction, and task prediction, resulting in a suboptimal end-to-end performance.
Unsupervised learning of MRI tissue properties using MRI physics models
In this work we propose an unsupervised deep-learning strategy that employs MRI physics to estimate all three tissue properties from a single multiecho MRI scan session, and generalizes across varying acquisition parameters.
Fast Infant MRI Skullstripping with Multiview 2D Convolutional Neural Networks
The three probabilistic segmentations in the three views are linearly fused and thresholded to produce a final brain mask.
A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology
In this study, we present a probabilistic atlas of the thalamic nuclei built using ex vivo brain MRI scans and histological data, as well as the application of the atlas to in vivo MRI segmentation.
