The paper presents a novel three-part taxonomy of regularization methods for medical image registration and identifies transfer gaps and evaluation weaknesses.
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From Model Based to Learned Regularization in Medical Image Registration: A Comprehensive Review
The paper presents a novel three-part taxonomy of regularization methods for medical image registration and identifies transfer gaps and evaluation weaknesses.