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Mutual Information (MI) has been extensively used as a similarity measure in image registration and motion estimation, and it is particularly robust for 3D multimodal medical image registration. However, MI estimators are known i) to have a high variance and ii) to be computationally costly. In order to overcome these drawbacks, we propose a new similarity(More)
The EMPIRE 10 challenge offers the opportunity to validate a non-rigid registration algorithm in the context of the difficult lung registration task. We propose a new similarity measure for this purpose, which is a Edgeworth-based third order approximation of Mutual Information (MI) and named 3-EMI. Athough this kind of expansion is well-known in(More)
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