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An Optimal Estimation Approach for the Registration of Time Series Abstract This paper discusses an optimal control approach for the registration of image time-series (growth modeling). It combines and augments work on an optimal control formulation to optical flow with theory from large-displacement diffeomorphic image registration. The unification of the two viewpoints leads to (i) a more efficient computation of the gradient of the optimization problem, (ii) an easier numerical implementation, and (iii) an intuitive interpretation of the adjoint equation underlying the optimization problem. Further, a novel formulation for the unbiased estimation of image correspondences across time is proposed. 
These images show the development of an artificially deformed brain over time. The test is set up so that there is 1 time unit between the first two measured images (a) and (b), and 2 time units between the second (b) and third (c) measured image. Full Paper
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