Self-supervised learning for spinal MRIs
A significant proportion of patients scanned in a clinical setting have follow-up scans. We show in this work that such longitudinal scans alone can be used as a form of “free” self-supervision for training a deep network. We demonstrate this self-supervised learning for the case of T2-weighted sagi...
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| Format: | Conference item |
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Springer, Cham
2017
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