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首页> 外文会议>Conference on Medical Imaging 2008: Imaging Processing; 20080217-19; San Diego,CA(US) >3D MRI Brain Image Segmentation Based on Region Restricted EM Algorithm
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3D MRI Brain Image Segmentation Based on Region Restricted EM Algorithm

机译：基于区域约束EM算法的3D MRI脑图像分割

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This paper presents a novel algorithm of 3D human brain tissue segmentation and classification in magnetic resonance image (MRI) based on region restricted EM algorithm (RREM). The RREM is a level set segmentation method while the evolution of the contours was driven by the force field composed by the probability density functions of the Gaussian models. Each tissue is modeled by one or more Gaussian models restricted by free shaped contour so that the Gaussian models are adaptive to the local intensities. The RREM is guaranteed to be convergency and achieving the local minimum. The segmentation avoids to be trapped in the local minimum by the split and merge operation. A fuzzy rule based classifier finally groups the regions belonging to the same tissue and forms the segmented 3D image of white matter (WM) and gray matter (GM) which are of major interest in numerous applications. The presented method can be extended to segment brain images with tumor or the images having part of the brain removed with the adjusted classifier.
机译：本文提出了一种基于区域受限EM算法（RREM）的磁共振图像（MRI）中3D人脑组织分割和分类的新算法。 RREM是一种水平集分割方法，而轮廓的演变是由由高斯模型的概率密度函数组成的力场驱动的。每个组织都通过一个或多个受自由形状轮廓限制的高斯模型来建模，以便使高斯模型适应局部强度。保证RREM具有收敛性并达到局部最小值。分割避免被分割和合并操作困在局部最小值中。最后，基于模糊规则的分类器将属于同一组织的区域进行分组，并形成白质（WM）和灰质（GM）的分段3D图像，这在许多应用中都引起了人们的极大兴趣。所提出的方法可以扩展为分割具有肿瘤的脑图像或利用调整后的分类器去除脑的一部分的图像。

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