An adaptive multi-resolution algorithm for motion estimation in medical image sequences

We propose an adaptive multi-resolution mean field annealing (MFA) algorithm for motion estimation in medical image sequences. The proposed algorithm can be easily parallelized and therefore is suitable to be implemented on dedicated hardware. The algorithm ensures a trade-off between precision and computational time, i.e. it ensures a good efficiency compared to other deterministic and stochastic algorithms. Results are reported for CT medical image sequences. The results are compared in terms of precision and computational time with those of other algorithms, such as the basic block-matching and Horn & Schunck algorithm, as well as with the mono-resolution and homogeneous multi-resolution MFA algorithm.