Recursive refinement network for deformable lung registration between exhale and inhale CT scans
Unsupervised learning-based medical image registration approaches have witnessed rapid
development in recent years. We propose to revisit a commonly ignored while simple and
well-established principle: recursive refinement of deformation vector fields across scales.
We introduce a recursive refinement network (RRN) for unsupervised medical image
registration, to extract multi-scale features, construct normalized local cost correlation
volume and recursively refine volumetric deformation vector fields. RRN achieves state of …
development in recent years. We propose to revisit a commonly ignored while simple and
well-established principle: recursive refinement of deformation vector fields across scales.
We introduce a recursive refinement network (RRN) for unsupervised medical image
registration, to extract multi-scale features, construct normalized local cost correlation
volume and recursively refine volumetric deformation vector fields. RRN achieves state of …
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