Li Bin, Chen Wufan
School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2009 Aug;26(4):861-5.
Multiple sclerosis (MS) is an inflammatory demyelinating disease that would damage central nervous system. There is a growing attention to the segmentation algorithms of MS Lesions. An MRF-based algorithm for MS lesions segmentation of T2-weighted MR brain images is developed by utilizing the morphological characteristics of MS lesion tissues. The regions circumscribed by white matter are extracted at first by MRF-based segmentation and region growing methods; the abstracted regions are then segmented again using MRF-based algorithm. The segmented MS lesions of both simulated and clinical T2-weighted MR brain images are presented in the current work. The testing results show that the proposed algorithm is robust and accurate enough for clinical use.
多发性硬化症（MS）是一种会损害中枢神经系统的炎性脱髓鞘疾病。人们对MS病灶的分割算法越来越关注。通过利用MS病灶组织的形态学特征，开发了一种基于马尔可夫随机场（MRF）的T2加权磁共振脑图像MS病灶分割算法。首先通过基于MRF的分割和区域生长方法提取由白质界定的区域；然后使用基于MRF的算法对提取的区域进行再次分割。当前工作展示了模拟和临床T2加权磁共振脑图像的分割MS病灶。测试结果表明，所提出的算法对于临床应用具有足够的鲁棒性和准确性。
