Groupwise image registration based on a total correlation dissimilarity measure for quantitative MRI and dynamic imaging data

Scientific Reports
Jean-Marie GuyaderS Klein

Abstract

The most widespread technique used to register sets of medical images consists of selecting one image as fixed reference, to which all remaining images are successively registered. This pairwise scheme requires one optimization procedure per pair of images to register. Pairwise mutual information is a common dissimilarity measure applied to a large variety of datasets. Alternative methods, called groupwise registrations, have been presented to register two or more images in a single optimization procedure, without the need of a reference image. Given the success of mutual information in pairwise registration, we adapt one of its multivariate versions, called total correlation, in a groupwise context. We justify the choice of total correlation among other multivariate versions of mutual information, and provide full implementation details. The resulting total correlation measure is remarkably close to measures previously proposed by Huizinga et al. based on principal component analysis. Our experiments, performed on five quantitative imaging datasets and on a dynamic CT imaging dataset, show that total correlation yields registration results that are comparable to Huizinga's methods. Total correlation has the advantage of being ...Continue Reading

References

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May 11, 2006·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·A LeemansP Parizel
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Jan 24, 2016·Medical Image Analysis·W HuizingaS Klein
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Citations

Apr 25, 2020·Sensors·Nefeli LamprinouEmmanouil Z Psarakis
Nov 9, 2020·Computer Methods and Programs in Biomedicine·Rosa-María Menchón-LaraCarlos Alberola-López

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BETA
PCA

Software Mentioned

mTRE
mathrm
mathop
elastix

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