Abstract：Automatic segmentation of brain magnetic resonance images is a critical problem in many medical imaging applications. In this paper, a robust automated segmentation algorithm is presented for the brain magnetic resonance images. The segmentation framework is composed of three stages. First, it uses level set method to perform the brain stripping operation. In the second stage, it compensates for nonuniformity in the brain image based on computing estimates of tissue intensity variation. Finally, a maximum aposteriori classifier is used to partition the brain into gray matter, white matter, and cerebrospinal fluid. The proposed method has been tested using magnetic resonance dada. This algorithm may be applied to various research and clinical investigations in which brain segmentation and volume measurement involving Magnetic resonance images dada are needed.
林盘; 郑崇勋; 杨勇; 阎相国; 顾建文. 一种鲁棒的人脑组织核磁共振图像分割算法研究[J]. 电子与信息学报, 2005, 27(9): 1420-1424 .
Lin Pan;Zheng ChongXun;Yang Yong;Yan XiangGuo;Gu JianWen. A Robust Method for Segmentation of Human Brain Tissue from Magnetic Resonance Images. , 2005, 27(9): 1420-1424 .
2005, Vol. 27 
