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In this paper, we present a framework for extracting mutually-salient landmark pairs for registration. Traditional methods detect landmarks one-by-one and separately in two images. Therefore, the detected landmarks might inherit low discriminability and are not necessarily good for matching. In contrast, our method detects landmarks pair-by-pair across images, and those pairs are required to be mutually-salient, i.e., uniquely corresponding to each other. The second merit of our framework is that, instead of finding individually optimal correspondence, which is a local approach and could cause self-intersection of the resultant deformation, our framework adopts a Markov-random-field (MRF)-based spatial arrangement to select the globally optimal landmark pairs. In this way, the geometric consistency of the correspondences is maintained and the resultant deformations are relatively smooth and topology-preserving. Promising experimental validation through a radiologist’s evaluation of the established correspondences is presented.
Landmark Detection, Landmark Matching, Image Registration, MRF, Mutual-Saliency
Ou, Y., Besbes, A., Bilello, M., Mansour, M., Davatzikos, C., & Paragios, N. (2010). Detecting Mutually-Salient Landmark Pairs with MRF Regularization. Retrieved from https://repository.upenn.edu/be_papers/153
Date Posted: 23 July 2010
This document has been peer reviewed.