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克服灰度不均匀性的脑MR图像分割模型

A Novel Model for Brain MR Images Segmentation in the Presence of Intensity Inhomogeneity

  • 摘要: 为了克服脑核磁共振图像中存在的灰度不均匀现象,提出一种有效的脑核磁共振图像分割模型.该模型利用多相位水平集方式来拟合图像的局部灰度,实现多种脑组织的同时分割,并提供光滑且准确的目标边界或曲面.在二维、三维的图像上的比较实验结果表明,该模型是有效的.

     

    Abstract: To overcome the difficulty caused by intensity in homogeneity in the segmentation of magnetic resonance (MR) images,this paper presents a new multiphase level set model for segmentation of brain MR images. The proposed model utilizes local image intensities,which enables it to cope with intensity inhomogeneity. The proposed model can extract brain white matter (WM),gray matter (GM) and cerebrospinal fluid (CSF) simultaneously and provide a smooth contour surface. Comparisons of 2D and 3D segmentation demonstrate the model's effectiveness.

     

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