Consistent landmark and intensity-based image registration

Two new consistent image registration algorithms are presented: one is based on matching corresponding landmarks and the other is based on matching both land-mark and intensity information. The consistent landmark and intensity registration algorithm produces good correspondences between images near landmark locations by matching corresponding landmarks and away from landmark locations by match-ing the image intensities. In contrast to similar unidirectional algorithms, these new consistent algorithms jointly estimate the forward and reverse transformation be-tween two images while minimizing the inverse consistency error—the error between the forward (reverse) transformation and the inverse of the the reverse (forward) transformation. This reduces the ambiguous correspondence between the forward and reverse transformations associated with large inverse consistency errors. In both algorithms a thin-plate spline model is used to regularize the estimated transforma-tions. Examples are presented that show the inverse consistency error produced by the traditional unidirectional landmark thin-plate spline algorithm can be rela-tively large and that this error is minimized using the consistent landmark algorithm. Results using MRI data are presented that demonstrate that using landmark and in-tensity information together produce better correspondence between medical images than using either landmarks or intensity information alone