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Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
Published on: October 27, 2023
This study derives the Cramér-Rao lower bound for affine transformation parameter estimation in heteroscedastic errors-in-variables models, crucial for accurate image registration, especially in fluorescence microscopy. Simplified bounds are provided for scalar covariance matrices, validated by simulations and experimental data.
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