"Semi-Automatic Construction of Reference Standards for Evaluation of Image Registration"

Keelin Murphy, Bram van Ginneken, Stefan Klein, Marius Staring, Max A. Viergever and Josien P.W. Pluim


Quantitative evaluation of image registration algorithms is a difficult and under-addressed issue due to the lack of a reference standard in most registration problems. In this work a method is presented whereby detailed reference standard data may be constructed in an efficient semi-automatic fashion. A well-distributed set of n landmarks is detected fully automatically in one scan of a pair to be registered. Using a custom-designed interface, observers define corresponding anatomic locations in the second scan for a specified subset of s of these landmarks. The remaining n - s landmarks are matched fully automatically by a thin-plate-spline based system using the s manual landmark correspondences to model the relationship between the scans. The method is applied to 47 pairs of temporal thoracic CT scans, three pairs of brain MR scans and five thoracic CT datasets with synthetic deformations. Interobserver differences are used to demonstrate the accuracy of the matched points. The utility of the reference standard data as a tool in evaluating registration is shown by the comparison of six sets of registration results on the 47 pairs of thoracic CT data.



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Copyright © 2011 by the authors. Published version © 2011 by Elsevier Science. 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

author = "{Keelin Murphy and Bram van Ginneken and Stefan Klein and Marius Staring and Max A. Viergever and Josien P.W. Pluim}",
title = "{Semi-Automatic Construction of Reference Standards for Evaluation of Image Registration}",
journal = "{Medical Image Analysis}",
volume = "{15}",
number = "{1}",
pages = "{71 - 84}",
month = "{February}",
year = "{2011}",

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