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"Confidence Estimation for Medical Image Registration Based On Stereo Confidences"

Gorkem Saygili, Marius Staring and Emile A. Hendriks

Abstract

In this paper, we propose a novel method to estimate the confidence of a registration that does not require any ground truth, is independent from the registration algorithm and the resulting confidence is correlated with the amount of registration error. We first apply a local search to match patterns between the registered image pairs. Local search induces a cost space per voxel which we explore further to estimate the confidence of the registration similar to confidence estimation algorithms for stereo matching. We test our method on both synthetically generated registration errors and on real registrations with ground truth. The experimental results show that our confidence measure can estimate registration errors and it is correlated with local errors.

 

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Copyright © 2016 by the authors. Published version © 2016 by IEEE. Personal use of this material is permitted. However, permission to reprint or republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the copyright holder.

 

BibTeX entry

@article{Saygili:2016,
author = "{Gorkem Saygili and Marius Staring and Emile A. Hendriks}",
title = "{Confidence Estimation for Medical Image Registration Based On Stereo Confidences}",
journal = "{IEEE Transactions on Medical Imaging}",
volume = "{35}",
number = "{2}",
pages = "{539 - 549}",
month = "{February}",
year = "{2016}",
}

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