Integrated Intensity and Point-Feature Nonrigid Registration.
In this work, we present a method for the integration of feature and intensity information for non rigid registration. Our method is based on a free-form deformation model, and uses a normalized mutual information intensity similarity metric to match intensities and the robust point matching framework to estimate feature (point) correspondences. The intensity and feature components of the registration are posed in a single energy functional with associated weights. We compare our method to both point-based and intensity-based registrations. In particular, we evaluate registration accuracy as measured by point landmark distances and image intensity similarity on a set of seventeen normal subjects. These results suggest that the integration of intensity and point-based registration is highly effective in yielding more accurate registrations.
Papademetris
Xenophon
X
Department of Biomedical Engineering, Yale University New Haven, CT 06520-8042.
Jackowski
Andrea P
AP
Schultz
Robert T
RT
Staib
Lawrence H
LH
Duncan
James S
JS
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