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2020
Conference Paper
Titel
Abstract: mlVIRNET: Improved deep learning registration using a coarse to fine approach to capture all levels of motion
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.