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Image Registration Accuracy Estimation Without Ground Truth Using Bootstrap

  • Conference paper
Computer Vision Approaches to Medical Image Analysis (CVAMIA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4241))

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.

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Author information

Authors and Affiliations

  1. Center for Machine Perception, Czech Technical University, Prague, Czech Republic

    Jan Kybic

  2. Faculty of Medicine I, Charles University, Prague, Czech Republic

    Daniel Smutek

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  1. Jan Kybic
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  2. Daniel Smutek
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Editor information

Editors and Affiliations

  1. Dept. of Electrical & Computer Engineering and Dept. of Internal Medicine, The University of Iowa, USA

    Reinhard R. Beichel

  2. Department of Electrical and Computer Engineering, University of Iowa, 52242, Iowa City, IA, USA

    Milan Sonka

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© 2006 Springer-Verlag Berlin Heidelberg

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Kybic, J., Smutek, D. (2006). Image Registration Accuracy Estimation Without Ground Truth Using Bootstrap. In: Beichel, R.R., Sonka, M. (eds) Computer Vision Approaches to Medical Image Analysis. CVAMIA 2006. Lecture Notes in Computer Science, vol 4241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11889762_6

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  • DOI: https://doi.org/10.1007/11889762_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46257-6

  • Online ISBN: 978-3-540-46258-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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