Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration
© Springer Nature Switzerland AG 2018. Traditional 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 facilitat...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer International Publishing,
2021-11-05T19:02:03Z.
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| Subjects: | |
| Online Access: | Get fulltext |