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An ITK-based Implementation of the Stochastic Rank Correlation (SRC) Metric

Steininger, Philipp, Neuner, Markus, Birkfellner, Wolfgang, Gendrin, Christelle, Mooslechner, Michaela, Bloch, Christoph, Pawiro, Supyianto, Sedlmayer, Felix, Deutschmann, Heinrich
Institute for Research and Development on Advanced Radiation Technologies (radART), Paracelsus Medical University (PMU), Salzburg, AUSTRIA
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3229
New: Prefer using the following doi: https://doi.org/10.54294/3qemyz
Published in The Insight Journal - 2010 July-December.
Submitted by Philipp Steininger on 2010-11-10 14:49:57.

Recently, Birkfellner et al. proposed a novel image-to-image merit function (stochastic rank correlation, SRC) for robust intensity-based 2D/3D image registration. In this work, we summarize the basic idea of SRC, and present a generic ITK-based implementation of this image-to-image metric including tests for software verification. Moreover, we provide two simple examples that demonstrate the usage of this metric: a) within the native ITK 2D/3D image registration method, and b) within a recently published extended ITK-based 2D/3D registration framework. It is, however, important to note, that this paper neither covers a comprehensive evaluation of SRC, nor a comparison with other metrics. It rather shows that SRC appears to succeed on a femoral and a porcine data set in the course of ITK-based 2D/3D image registration.