Predicting medical image registration error with block-matching using three orthogonal planes approach

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Estimating registration error is a crucial task in medical image registration. Although successful algorithms have been proposed, non-trivial challenges still exist such as lacking available data with ground truth and excessive computational load sourcing from the processing of 3D image volume. This paper presents an algorithm that can estimate target registration error accurately with fewer computations by using block-matching on three orthogonal planes rather than on a 3D volume. Furthermore, we present a way of using stereo datasets and stereo matching algorithms for predicting medical image registration error. Both contributions alleviate two crucial problems (lacking ground truth and excessive computational load) in the field of error estimation for medical image registration.