Human brain extraction from T2 weighted volumetric magnetic resonance images

ZHANG Guang-cai; FU Yi-li; WANG Shu-guo; GAO Wen-peng; JIA Xiao-lan

doi:10.3788/OPE.20111907.1635

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Human brain extraction from T2 weighted volumetric magnetic resonance images

Article | 更新时间：2020-08-12

- Human brain extraction from T2 weighted volumetric magnetic resonance images
- Optics and Precision Engineering Vol. 19, Issue 7, Pages: 1635-1642(2011)
- 作者机构：
  
  哈尔滨工业大学机器人技术与系统国家重点实验室,黑龙江哈尔滨,150080
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20111907.1635
  CLC： TP391.4
- Received：06 September 2010，
  
  Revised：29 November 2010，
  
  Published Online：25 July 2011，
  
  Published：25 July 2011
- 稿件说明：
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张广才, 付宜利, 王树国, 高文朋, 贾晓岚. T2加权人脑MR体数据的脑提取[J]. 光学精密工程, 2011,19(7): 1635-1642

ZHANG Guang-cai, FU Yi-li, WANG Shu-guo, GAO Wen-peng, JIA Xiao-lan. Human brain extraction from T2 weighted volumetric magnetic resonance images[J]. Editorial Office of Optics and Precision Engineering, 2011,19(7): 1635-1642
张广才, 付宜利, 王树国, 高文朋, 贾晓岚. T2加权人脑MR体数据的脑提取[J]. 光学精密工程, 2011,19(7): 1635-1642 DOI： 10.3788/OPE.20111907.1635.

ZHANG Guang-cai, FU Yi-li, WANG Shu-guo, GAO Wen-peng, JIA Xiao-lan. Human brain extraction from T2 weighted volumetric magnetic resonance images[J]. Editorial Office of Optics and Precision Engineering, 2011,19(7): 1635-1642 DOI： 10.3788/OPE.20111907.1635.

摘要

为了实现人脑T2加权MR图像的脑组织和非脑组织的分割

提出了一种基于三维形变曲面模型和数学形态学算法的MR T2图像脑提取方法。该方法分为两级提取:第一级提取依据脑解剖学知识

影像学知识及T2加权MR脑图像的组织在灰度直方图中的分布规律

应用三维形变曲面模型和区域生长实现脑的初级提取;第二级提取则根据图像的局部信息

应用六邻域结构元素对脑初级提取结果进行数学形态学处理

使脑提取结果更精确。实验结果表明

使用该方法对人脑T2加权MR数据进行脑提取的准确率能达到94%以上。算法性能评估证明本算法能够比较好地实现T2加权MR图像的脑提取。

Abstract

For the segmentation of the non-brain tissues and brain tissues from the T2 weighted volumetric Magnetic Resonance Images (MRI)

an image extraction method including two levels was proposed to extract brain tissues based on deformable surface models and mathematical morphology. The first level was finished by deformable surface models and region growing according to the brain anatomic

imaging knowledge

and the distribution of MR brain tissues in intensity histogram; the second level was completed by using mathematical morphology to erode the outcome of the first level of brain extraction to obtain more precise results. The experimental results demonstrate that the accuracy rate of the human brain extraction from T2 weighted MRI can reach more than 94%. The algorithm performance evaluation proofs that the proposed method is effective on the extraction of brain tissues from T2 weighted MRIs.

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references

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