全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

量子衍生PDE医学超声图像去斑

DOI: 10.11834/jig.20150113

Keywords: 量子衍生,偏微分方程(PDE),医学超声图像,去斑

Full-Text   Cite this paper   Add to My Lib

Abstract:

目的医学超声图像常常受到斑点噪声的污染而导致质量降低,影响后续诊疗。为了解决医学超声图像在滤波去斑的同时保持图像边缘细节和结构特征的问题,借鉴量子力学的基础理论,提出一种量子衍生偏微分方程(PDE)医学超声图像去斑方法。方法针对传统P-M方程各向异性扩散的自适应去斑能力有限的问题,引入量子理论改进扩散系数增强去斑算法的自适应能力。同时构造出各向异性扩散模型,提出一种量子衍生的偏微分方程医学超声图像去斑方法。结果通过对模拟斑点噪声污染的图像和真实医学超声图像实验,比较信噪比(SNR)、边缘保持度、结构相似度(SSIM)等客观评价指标,本文方法较其他图像去斑方法更能有效去除斑点噪声,同时又能较好地保持图像边缘细节与结构特征。结论本文方法能够有效地解决医学超声图像去斑中保持图像细节特征的问题,同时,量子理论的引入也为后续医学超声图像的研究提供了新思路。

References

[1]  Fu X W, Ding M Y, Cai C. Despeckling of medical ultrasound images based on quantum-inspired adaptive threshold[J]. Electronics Letters, 2010, 46(13): 889-891. [DOI: 10.1049/el.2010.1092]
[2]  Dabov K, Foi A, Katkovnik V, et al. Image denoising by sparse 3-D transform-domain collaborative filtering[J]. IEEE Transactions on Image Processing, 2007, 16(8): 2080-2095. [DOI: 10.1109/TIP.2007.901238]
[3]  Tian J, Chen L. Image despeckling using a non-parametric statistical model of wavelet coefficients[J]. Biomedical Signal Processing and Control, 2011, 6(4): 432-437. [DOI: 10.1016/j.bspc.2010.11.006]
[4]  Perona P, Malik J. Scale-space and edge detection using anisotropic diffusion[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(7): 629-639. [DOI: 10. 1109/34.56205]
[5]  Catté F, Lions P L, Morel J M, et al. Image selective smoothing and edge detection by nonlinear diffusion[J]. SIAM Journal on Numerical Analysis, 1992, 29(1): 182-193. [DOI: 10.1137/0729012]
[6]  Eldar Y C, Oppenheim A V. Quantum signal processing[J]. IEEE Signal Processing Magazine, 2002, 19(6): 12-32. [DOI: 10. 1109/MSP.2002.1043298]
[7]  Zhang J, Li H, Tang Z, et al. An improved quantum-inspired genetic algorithm for image multilevel thresholding segmentation[J]. Mathematical Problems in Engineering, 2014:295402(1-12).[DOI: 10.1155/2014/295402]
[8]  Dey S, Saha I, Bhattacharyya S, et al. Multi-level thresholding using quantum inspired meta-heuristics[J]. Knowledge-Based Systems, 2014, 67:373-400.[DOI: 10.1016/j.knosys. 2014. 04.006]
[9]  Xie K F, Luo A. Research on quantum-inspired mathematical morphology[J]. Acta Electronica Sinica, 2005, 33(2): 284-287. [谢可夫, 罗安. 量子启发数学形态学的研究[J]. 电子学报, 2005, 33(2): 284-287.] [DOI: 10.3321/j.issn:0372-2112.2005.02.022]
[10]  Xie K F, Luo A, Zhou X Y. Morphological method inspired by quantum for edge detection of image[J]. Compter Engineering and Applications, 2007, 43(11): 87-89. [谢可夫, 罗安, 周心一. 量子衍生形态学图像边缘检测方法[J]. 计算机工程与应用, 2007, 43(11): 87-89.] [DOI: 10.3321/j.issn:1002-8331.2007.11.030]
[11]  Xie K F, Zhou X Y, Xu G P. Morphology filtering inspired by quantum collapsing[J]. Journal of Image and Graphics,2009, 14(5): 967-972. [谢可夫, 周心一, 许光平. 量子衍生坍缩形态学滤波[J]. 中国图象图形学报,2009, 14(5): 967-972.] [DOI: 10.11834/jig.20090530]
[12]  Fu X W, Ding M Y, Zhou C P, et al. Research on image enhancement algorithms of medical images based on quantum probability statistics[J]. Acta Electronica Sinica, 2010, 38(7): 1590-1596. [付晓薇, 丁明跃, 周成平, 等. 基于量子概率统计的医学图像增强算法研究[J]. 电子学报, 2010, 38(7): 1590-1596.]

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133