Summary: An alternative to the accelerated failure time model is to regress the median of the failure time on the covariates. In recent years, censored median regression models have been shown to be useful for analyzing a variety of censored survival data with the robustness property. Based on the missing information principle, a semiparametric inference procedure for regression parameters has been developed when the censoring variable depends on continuous covariates. In order to improve the low coverage accuracy of such procedure, we apply an empirical likelihood ratio method (EL) to the model and derive the limiting distributions of the estimated and adjusted empirical likelihood ratios for the vector of regression parameters. Two kinds of EL confidence regions for the unknown vector of regression parameters are obtained accordingly. We conduct an extensive simulation study to compare the performance of the proposed methods with the normal approximation based method. The simulation results suggest that the EL methods outperform the normal approximation based method in terms of coverage probability. Finally, we make some discussions about our methods.