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  4. A Level Set Based Deformable Model for Skull-Stripping Brain MR Images
 
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A Level Set Based Deformable Model for Skull-Stripping Brain MR Images

Date Issued
2014
Date
2014
Author(s)
Su, Chien-Ming
URI
http://ntur.lib.ntu.edu.tw//handle/246246/260919
Abstract
Segmentation of brain tissue from non-brain tissue, also known as skull stripping, has been challenging due to the complexity of human brain structures and variable parameters of MR scanners. It is one of the most important preprocessing steps in medical image analysis. We propose a new brain segmentation algorithm that is based on a level set based deformable model. Two different forces are used to guide the evolution of the level set contour. The brain surface attraction force is calculated based on the intensity values of the brain, which is designed to automatically adjust the intrinsic parameters in response to different slices. The other force is a morphological smoothing force based on the mean curvature and weighted by the differences between the mean intensities inside and outside the contour and the zero level set intensities. Experimental results indicated that the proposed algorithm is effectively accurate and robust, which is a promising tool in many skull stripping applications.
Subjects
影像分割
水平集方法
腦部
頭骨去除
磁振影像
Type
thesis
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ntu-103-R01525080-1.pdf

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(MD5):2f54d354068d1f3676a1b78aee01b33d

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