Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces
Classical deformable registration techniques achieve impressive results and offer a rigorous theoretical treatment, but are computationally intensive since they solve an optimization problem for each image pair. Recently, learning-based methods have facilitated fast registration by learning spatial...
Main Authors: | , , |
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Other Authors: | , |
Format: | Article |
Language: | English |
Published: |
Elsevier BV,
2021-01-22T15:28:31Z.
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Subjects: | |
Online Access: | Get fulltext |