Segmentation of MR Image Based on Maximum A Posterior.

摘要

Brain MR image segmentation takes an important role in research and clinical application. Statistical method is effective in the segmentation, which is usually based on maximum a posterior (MAP). The key of MAP method is to estimate a prior probability of the segmentation. Multilevel logistic (MLL) model has been used in practice for the estimation. To farther improve the performance of the segmentation, a weighted MLL (WMLL) model is proposed in this paper. The simulated results show that the WMLL model is effective.