Misdirected Registration Uncertainty
This work addresses a fundamental methodological issue in probabilistic medical image registration, which could impact researchers and practitioners in medical imaging.
The paper argues that using transformation uncertainty to quantify registration uncertainty in medical image registration is inappropriate and misleading, and questions the practice of determining voxel correspondence solely by the mode of the transformation distribution.
Being a task of establishing spatial correspondences, medical image registration is often formalized as finding the optimal transformation that best aligns two images. Since the transformation is such an essential component of registration, most existing researches conventionally quantify the registration uncertainty, which is the confidence in the estimated spatial correspondences, by the transformation uncertainty. In this paper, we give concrete examples and reveal that using the transformation uncertainty to quantify the registration uncertainty is inappropriate and sometimes misleading. Based on this finding, we also raise attention to an important yet subtle aspect of probabilistic image registration, that is whether it is reasonable to determine the correspondence of a registered voxel solely by the mode of its transformation distribution.