
Contributions to the Normalized Correlation and the Mean Squares Metric
Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/190 |
Published in The Insight Journal - 2006 January - June.
Submitted by Marius Staring on 07-21-2006.
This document describes contributions on the
NormalizedCorrelationImageToImageMetric and the MeanSquaresImageToImageMetric of the Insight Toolkit ITK url{www.itk.org}. For the first metric a two time speed-up can be
achieved by rewriting the code to loop only once over the fixed image. This is instead of the two times that is used in the current ITK code. The reduction in computation time comes at the cost of an additional storage of a parameters array. For both metric we have
implemented the option to use only a random subset of the fixed image voxels for calculating the metric value and its derivatives. This reduces the computation time (substantially), while convergence
properties are maintained. This paper is accompanied with the source code.
NormalizedCorrelationImageToImageMetric and the MeanSquaresImageToImageMetric of the Insight Toolkit ITK url{www.itk.org}. For the first metric a two time speed-up can be
achieved by rewriting the code to loop only once over the fixed image. This is instead of the two times that is used in the current ITK code. The reduction in computation time comes at the cost of an additional storage of a parameters array. For both metric we have
implemented the option to use only a random subset of the fixed image voxels for calculating the metric value and its derivatives. This reduces the computation time (substantially), while convergence
properties are maintained. This paper is accompanied with the source code.
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Categories: | Programming |
Keywords: | Normalized Correlation, Mean Square Difference |
Toolkits: | ITK, CMake |
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