期刊文献+

基于偏微分方程的医学磁共振图像去噪 被引量:4

Pde-Based MRI Image Denoising
下载PDF
导出
摘要 本文引入了基于偏微分方程的Perona-Malik模型,并结合了Catte的高斯扩散滤波器的概念,给出了一种针对医学磁共振图像去噪的方法及其实现。文中通过给出不同参数,对结果加以比较分析。把该方法应用于医学图像去噪,得到比较令人满意的结果。 A PDE-based Perona-Malik model was introduced in this paper. Combined with the idea first presental by Catte about Gaussian diffesion filter, a method for MRI image denoising was presented with its realization. According to different parameters given, results were compared and analyzed. The method was applied to medical images and its results were encouraging.
出处 《信号处理》 CSCD 2004年第3期318-321,共4页 Journal of Signal Processing
关键词 医学诊断 磁共振图像 图像去噪 偏微分方程 Perona-Malik模型 anisotropic diffusion image denoising MRI perona-malik model
  • 相关文献

参考文献8

  • 1G. Gerig, O. Kubler. Nonlinear anisotropic filtering of MRI data, IEEE TRANS. ON MEDICAL IMAGING,VOL. 11. NO,2. JUNE 1992.
  • 2F, Goddiebsen, A Study of Image Inprovement Techni-ques Applied to NMR Images, Ph.D. thesis, The Norwegian Insfitum of technology (NTNU), Division of Mathematical Sciences, September 1989.
  • 3H. Soltanian-Zadeh, Feature space analysis in MRI, in Signal Processing for magnetic Resonance Imaging and speclxoscopy, H. Yaa, Ed., pp255-315,Marcel Dekker,New York, 2002.
  • 4J. Black, H, Marlmont, Robust anisotropic diffusion,IEEE TRANS. ON IMAGE PROCESSING, VOL. 7, NO,3,MARCH 1998.
  • 5P. Pemna, J, Malik, ScsJe-space and edge detection using anisotropic diffusion, IEE.E TRANS. Pattern AnalMachine Intell. 12(7):629-639,1990.
  • 6A. Witkin, Scale-space fdtering, Int, Joint conf. Artif.Intell., pp.1019-1021, Kadsrahe, west Germany, 1983.
  • 7A. Hunmlel, Rc:presemafions based on zero-crossing in scale-space, Proc, IEEE Computer Vision and Pattern Recog. Conf.:204-209,1986.
  • 8E Carte et al, Image selective smoothing and edge detec-tion by nonlinear diffusion. SIAM J.Numer, Anal.,29(1):182-193,1992.

同被引文献20

  • 1张启明.寒热证阴阳变化的模拟分析[J].辽宁中医杂志,1995,22(11):480-484. 被引量:7
  • 2王新楼,乔明,邹谋炎.一种基于偏微分方程的SAR图像去噪方法[J].电子与信息学报,2005,27(9):1365-1369. 被引量:8
  • 3董骝焕,袁媛,沈世镒,孙保存,倪春生.使用线性微分方程构建初步的乳腺癌转移相关基因网络模型[J].生物数学学报,2007,22(1):46-52. 被引量:4
  • 4Tikhonov A N. Regularization of incorrectly posed problems[J]. Soviet. Math. Dokl, 1963, 4: 1624-1627.
  • 5Perona P and Malik J. Scale.space and edge detection using anisotropic diffusion[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(7): 629-639.
  • 6Charbonnier P, Aubert G, Barlaud Met al. Two deterministic half-quadratlc regularization algorithms for computed imaging[C]//Proceedings of the International Conference on Image Processing, 1994, 2: 168-172.
  • 7Geman S and McClure D E. Bayesian image analysis: an application to single photon emission tomography[J]. Amer. Statist. Assoc., 1985: 12-18.
  • 8Rudin L, Osher S, and Fatemi E. Nonlinear total variation based noise removal algorithms[J]. Physica D, 1992, 60: 259-268.
  • 9Green P J. Bayesian reconstruction from emission tomography data using a modified algorithm[J]. IEEE Trans. Med. Imaging, March 1990, 9(1): 84-93.
  • 10Kornprobst P, Deriche R, and Aubert G. Nonlinear operators in image restoration[C]//Proceedings of the International Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, IEEE. Puerto Rico, 1997: 325-331.

引证文献4

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部