
An ITK-based Implementation of the Stochastic Rank Correlation (SRC) Metric
Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3229 |
Published in The Insight Journal - 2010 July-December.
Submitted by Philipp Steininger on 11-10-2010.
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.
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Categories: | Filtering, Registration, Registration metrics |
Keywords: | metric, 2d/3d image registration, intensity-based, stochastic rank correlation, SRC, ITK |
Toolkits: | CMake, ITK, CMake, ITK |
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![]() by Hawley J., Johnson H.
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![]() by Vercauteren T., Pennec X., Perchant A., Ayache N.
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A lot of errors during building with Visual Studio 2010... Doesn't work at all :(