Registration technology can effectively integrate the prior knowledge of medical atlases into the segmentation process

and then combine with the efficient label fusion algorithm to obtain the segmentation results accurately and automatically.Aimed at the large error in registration of target image and its great influence on label fusion

a framework of probabilistic graphical model is established and the idea of multi-parameter registration model is proposed.Combined with an efficient algorithm on label fusion

this framework can improve the segmentation accuracy of specific tissue regions on target image

which has important application value in segmentation with a few available atlases.After the multi-parameter registration and the reconstruction process of training sets on target images

the final segmentation results are obtained by an efficient fusion algorithm.According to the experiment which was conducted on the brain magnetic resonance image segmentation with different segmentation methods

the proposed framework can effectively improve the accuracy of segmentation.