Image registration accuracy estimation without ground truth using bootstrap

Authors:
Jan Kybic;Daniel Smutek
Affiliations:
Center for Machine Perception, Czech Technical University, Prague, Czech Republic;Faculty of Medicine I, Charles University, Prague, Czech Republic
Venue:
CVAMIA'06 Proceedings of the Second ECCV international conference on Computer Vision Approaches to Medical Image Analysis
Year:
2006

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Abstract

We consider the problem of estimating the local accuracy of image registration when no ground truth data is available. The technique is based on a statistical resampling technique called bootstrap. Only the two input images are used, no other data are needed. The general bootstrap uncertainty estimation framework described here is in principle applicable to most of the existing pixel based registration techniques. In practice, a large computing power is required. We present experimental results for a block matching method on an ultrasound image sequence for elastography with both known and unknown deformation field.