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Cramér-Rao Lower Bound for Point Based Image Registration with Heteroscedastic Error Model for Application in Single Molecule Microscopy

The Cramér-Rao lower bound for the estimation of the affine transformation parameters in a multivariate heteroscedastic errors-in-variables model is derived. The model is suitable for feature-based image registration in which both sets of control points are localized with errors whose covariance mat...

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Détails bibliographiques
Publié dans:IEEE Trans Med Imaging
Auteurs principaux: Cohen, E.A.K., Kim, D., Ober, R.J.
Format: Artigo
Langue:Inglês
Publié: 2015
Sujets:
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC4673898/
https://ncbi.nlm.nih.gov/pubmed/26641728
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2015.2451513
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