一种新的脑白质分割方法

基于扩散张量成像提出一种新的脑白质分割方法.首先,计算扩散张量成像的各向异性参数和扩散参数,并得到各个参数下的脑部图像;然后,通过期望值最大化（expectation maximization,EM）模型求得各个各向异性参数图像的脑白质和非脑白质区域;最后,通过STAPLE（simultaneous truth and performancel evel estimation）模型融合各个DTI参数图像分割结果,得到脑白质分割结果.实验结果表明,该方法具有较好的分割效果,能有效地从脑组织中分割出脑白质.

A New Method of Brain White Matter Segmentation

A novel brain structure segmentation algorithm based on diffusion tensor imaging(DTI),which can extract white matter(WM) is presented.First,DTI diffusion and anisotropy parameters are computed to achieve brain images of each DTI parameter channel.Then,using the expectation maximization(EM) model,WM/non-WM regions in the anisotropy parameters channel are calculated.Finally,using simultaneous truth and performance level estimation(STAPLE) model,segmentation results of each DTI parameter image are fused to achieve the final brain white matter structure segmentation results.Experiments’ results showed that the algorithm can accurately segment,WM in brain structures.