An anisotropic virtual human brain image segmentation model
Luo Chun-yan · Journal of Nanjing University of Information Science & Technology · 2010
Virtual brain tissue information extraction has become an important part of virtual human brain data analysis.However,traditional extraction methods cannot obtain satisfactory results for image noise and lower layer data distraction.In this paper,RGB,HSL and HSV space information were used to construct a new information field,which can reduce the impact of lower layer data.Then an anisotropic Gibbs field was built with structure tensor information to reduce the effect of noise.The improved FCM model with anisotropic Gibbs field was introduced to segment image,in order to minimize the error caused by intensity inhomogeneity.Experiment results indicated that the method we proposed can obtain preferable segmentation results.