lower even if the coregistrations of a c and b c have an expected error greater than that of coregistration of a b the method still works well with more than three images and then gives even higher gains let each image be a node in a graph a calculated co registration between two images forms an edge between corresponding nodes each image is thus registered on each other image a coregistration between two selected images is obtained as the weighted mean value of all paths between the images nodes where the weights are calculated from an estimation of the variance of each registration and is chosen so as to minimize the variance in the result the deviation between the different paths can be used as a measure of the quality of the registration if landmark based registration is used then any of the the usual error estimates could be used to estimate the variance of each registration otherwise an estimation using the images 39 voxel size could be used the expected error of the resulting registration is always lower compared with the direct registration fig2 shows such a graph image a is denoted at 100 image b at 102 and image c at 104 the direct registration vector from a to b is shown as edge 106 however it will be seen that it is also possible to reach b via image c i e from 100 via edge 108 to image c at 104 then via edge 110 to reach image b at 102 as shown in fig3 an enlarged part of fig2 image b lies somewhere in the region denoted 102 u2032 the end points of registration vectors 106 and 110 do not co incide exactly there is a gap 112 between.