计算机应用 ›› 2013, Vol. 33 ›› Issue (05): 1439-1442.DOI: 10.3724/SP.J.1087.2013.01439

• 多媒体处理技术 • 上一篇    下一篇

脑部MRI图像头皮三维提取及重建

马阿敏1,杨荣骞1,宁海1,白红民2,黎丽华1,吴效明1   

  1. 1. 华南理工大学 生物科学与工程学院,广州 510006
    2. 广州军区广州总医院 神经外科,广州 510010
  • 收稿日期:2012-11-21 修回日期:2012-12-18 出版日期:2013-05-01 发布日期:2013-05-08
  • 通讯作者: 杨荣骞
  • 作者简介:马阿敏(1989-),女,河南许昌人,硕士研究生,主要研究方向:医学图像处理;杨荣骞(1979-),男,江西修水人,副教授,博士,主要研究方向:医学图像处理;宁海(1988-),男,安徽亳州人,硕士研究生,主要研究方向:医学图像处理。
  • 基金资助:

    国家自然科学基金青年基金资助项目(81101130);广东省自然科学基金资助项目(S2012010010652);华南理工大学中央高校基本业务费重点项目(2012ZZ0095)

3D scalp extraction and reconstruction of MRI brain images

MA AAmin1,YANG Rongqian1,NING Hai1,BAI Hongmin2,LI Lihua1,WU Xiaoming1   

  1. 1. School of Bioscience and Bioengineering, South China University of Technology, Guangzhou Guangdong 510006, China
    2. Department of Neurosurgery, Guangzhou General Hospital, Guangzhou Military Region of PLA, Guangzhou Guangdong 510010, China
  • Received:2012-11-21 Revised:2012-12-18 Online:2013-05-08 Published:2013-05-01
  • Contact: YANG Rongqian

摘要: 开颅手术中,为了满足手术导航系统进行快速、准确定位的要求,提出一种脑部核磁共振成像(MRI)图像三维头皮轮廓提取方法。首先采用各向异性扩散滤波方法对图像滤波,借助BrainSuite3医学软件获取脑标记图像;然后将图像中脑实质部分剔除,根据非脑组织图像计算头皮组织的分割阈值;再利用数学形态学处理二值图像获取头皮轮廓;最后结合目标灰度信息,用移动立方体(MC)算法进行三维重建。实验结果表明,该方法结合阈值、数学形态学和MC算法,能连续、光滑地提取出头皮外轮廓,并使精度达到亚像素级别。

关键词: 核磁共振成像图像分割, 各向异性扩散滤波, 数学形态学, 三维头皮提取, 亚像素, 移动立方体算法

Abstract: A new scalp extraction method for Magnetic Resonance Imaging (MRI) brain images in 3D was proposed for the requirements of image guided surgery on fast and accurate positioning in craniotomy. Firstly, anisotropic diffusion filtering was used to reduce noises, and the brain parenchyma image was got by the medical software of BrainSuite3. Afterwards, the brain parenchyma was removed and the threshold of scalp from non-brain-image was calculated. Thirdly, outside surface was extracted by mathematical morphology. Finally, combined with the gray value of scalp, the scalp was reconstructed by Marching Cube (MC) algorithm. The experiments show that this method can extract scalp effectively and the precision reaches sub-pixel's level by connecting threshold, mathematical morphology and MC algorithm.

Key words: Magnetic Resonance Imaging (MRI) segmentation, anisotropic diffusion filtering, mathematical morphology, 3D scalp extraction, sub-pixel, Marching Cube (MC) algorithm

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