Authors:
Mads F. Hansen
;
Thomas H. Mosbech
;
Hildur Ólafsdóttir
;
Michael S. Hansen
and
Rasmus Larsen
Affiliation:
Technical University of Denmark, Denmark
Keyword(s):
Image reconstruction, Image registration, Riemannian elasticity, Super resolution penalization prior.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Enhancement and Restoration
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Image Formation, Acquisition Devices and Sensors
;
Image Quality
;
Image Registration
Abstract:
This paper presents a novel method for upsampling anisotropic medical gray-scale images. The resolution is increased by fitting an image function, modeled by cubic B-splines, to the slices. The method simulates the observed slices with an image function and iteratively updates the function by comparing the simulated slices with observed slices. The approach handles partial voluming by modeling the thickness of the slices. The formulation is ill-posed, and thus a prior needs to be included. Correspondences between adjacent slices are established using a symmetric registration method with a free-form deformation model. The correspondences are then converted into a prior that penalizes gradients along lines of correspondence. Tests on the Shepp-Logan phantom show promising results, and the approach performs better than methods such as cubic interpolation and one-way registration-based interpolation.