准确定位大脑中的功能区域需要我们对fMRI图像中头骨等生物组织精确提取,但由于核磁共振仪等现有条件的限制,头骨等弱边缘信息难于提取。针对这一问题,提出一种弱边缘提取的有效方法。首先利用Mean-shift聚类特性,在不损失目标信息的情况下,削弱图像中的噪声干扰;根据滤波后像素灰度的区域分布特性,对头骨区域进行直方图增强,最后应用边缘检测算法将头骨边缘提取出来。实验的结果表明,该方法可以有效地将fMRI图像中的头骨弱边缘信息提取出来。

In order to orientate the function area in brain,an accurate skull extraction method is needed in fMRI image processing.But,we often miss the weak edge information in the skull fMRI image because of the existing imitations of MRI and conditions.For this problem,an efficient weak edge extraction method is proposed in this paper.On the premise of none of the target information losing,we first use mean-shift clustering algorithm to weaken the noise of the image.Then,based on the distribution features of the filtered images,a histogram enhancement method is used to enhance the skull area.At last,use canny edge detection algorithm to detect the edge of the skull in fMRI image.The experiment results represent that the method can extract the weak edge of the skull in fMRI images efficiently.