Automatic Multimodal Brain-tumor Segmentation
Brain-tumor segmentation method is an important clinical requirement for the brain-tumor diagnosis and the radiotherapy planning.But the number of clusters is very difficult to define for high diversity in the appearance of tumor tissue among the different patients and the ambiguous boundaries about the lesions.In our study,the nonparametric mixture of Dirichlet process (MDP) model is used to segment the tumor images automatically,which can be performed without initialization of the clustering number.Furthermore,the anisotropic diffusion and Markov random field (MRF) smooth constraint are both proposed in our study.Our segmentation results for the multimodal MR glioma image sequences showed the properties,such as accuracy and computing speed about our algorithm demonstrates very impressive.
image segmentation Multimodal Brain-tumor Dirichlet process anisotropic diffusion Markov random field
Yisu Lu Wufan Chen
Electronic Engineering Department South China Institute of Software Engineering.GU Guangzhou, China Key Lab for Medical Image Processing Southern Medical University Guangzhou, China
国际会议
秦皇岛
英文
939-942
2015-09-18（万方平台首次上网日期，不代表论文的发表时间）