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Image registration similarity measure

Much of the current work on biomedical image registration utilises voxel similarity measures in particular, mutual information based on the Shannon definition of entropy. The mutual information (MI) concept comes from information theory, measuring the dependence between two variables or, in other words, the amount of information that one variable contains about the other. The mutual information measures the relationship between two random variables, i.e. intensity values in two images if the two variables are independent, MI is equal to 0. If one variable provides some information about the second one, the MI becomes > 0. The MI is related to the image entropy by ... [Pg.82]

To measure the accuracy of the proposed method in our calibration procedure, a target registration error (TRE) [15, 16] and a fiducial registration error (FRE) [15] are computed. A fiducial point set with 40 pairs of image-physical points was collected. Similarly, a target point set with 40 pairs was stored. The FRE and TRE comparisons between our method and LM... [Pg.718]


See other pages where Image registration similarity measure is mentioned: [Pg.86]    [Pg.121]    [Pg.12]    [Pg.84]    [Pg.303]    [Pg.97]    [Pg.123]    [Pg.473]    [Pg.119]    [Pg.756]    [Pg.39]    [Pg.658]   
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