Abstract
While deep learning has become a methodology of choice in many areas, relatively few deep-learning-based image registration algorithms have been proposed. One reason for this is lack of ground-truth and the large variability of plausible deformations that can align corresponding anatomies. Therefore, the problem is much less constrained than for example image classification or segmentation.
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CITATION STYLE
Hering, A., & Heldmann, S. (2020). Abstract: Mlvirnet: Improved deep learning registration using a coarse to fine approach to capture all levels of motion. In Informatik aktuell (p. 175). Springer. https://doi.org/10.1007/978-3-658-29267-6_35
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