Improved nearest neighbor interpolators based on confidence region in medical image registration

摘要

In order to reduce artifacts in match metric and improve the registration speed in medical image registration, three types of improved nearest neighbor (NN) interpolators based on confidence region (CR) are studied. These improved NN interpolators include: (1) NN based on deterministic confidence region (DCR), DCRNN; (2) NN based on stochastic confidence region (SCR), SCRNN; (3) NN based on confidence region integrating deterministic information and stochastic information (DSCR), DSCRNN. The values of normalized mutual information (NMI) are deterministic and accurate at any grid translation position when any improved NN interpolator is used. The smoothness of the NMI curves is compared by applying DCRNN, SCRNN, and DSCRNN interpolators to rigid medical image registration with different numbers of intensity bins and random variables. The results of tests show that the new DSCRNN interpolator outperforms DCRNN and SCRNN in curve smoothness and anti-micro-fluctuation, and outperforms the conditional NN, PVI and LI interpolators in convergence performance and noise immunity.