PSEUDO-OPTICAL FLOW ESTIMATION FOR MEDICAL IMAGE SEQUENCE

摘要

In this paper, a statistical method is used to accomplish pseudo-optical flow estimation of medical image sequence. The optical flow field are modelled by a two-dimensional Gibbs random field (GRF). An estimation algorithm, based on the statistical model, approximately can find the maximum a posteriori (MAP) estimation of the optical flow field. The algorithm utilized for estimation is based on the iterative conditional modes (ICM) algorithm, which converges to the solution that maximizes the local conditional probabilities. Application of the algorithm can greatly reduce the inter-frame redundancies, thus faciliates the medical image compression.