期刊文献+

结合各向异性扩散滤波Thin Plate先验正电子发射断层图像重建的算法

Image reconstruction algorithm for positron emission tomography with Thin Plate prior combined with an anisotropic diffusion filter
下载PDF
导出
摘要 背景:在正电子发射断层成像中,MAP重建方法通过引入先验分布约束,可以明显提高重建图像的质量,但不合适的先验分布项可能会造成重建图像过度平滑或出现阶梯状边缘伪影。目的:针对基于传统局部先验信息的MAP方法易于导致重建图像过平滑或产生阶梯状边缘伪影的问题,提出了一种结合各向异性扩散滤波的、基于Thin Plate先验的改进MAP重建算法。方法:重建算法由两步组成:基于双向扩散系数的PDE各向异性扩散滤波和基于Thin Plate先验的MAP估计。重建图像通过这两步交替迭代得到。文中采用归一化均方根误差和信噪比定量评价重建图像质量。结果与结论:结合了基于双向扩散系数的PDE各向异性扩散滤波,并将Thin Plate二次二阶先验模型引入到MAP重建算法中,所获得的重建结果图像在抑制噪声、边缘保持方面取得了良好的效果,SNR、RMSE以及视觉评价等方面均有较大程度的改善。 BACKGROUND: In positron emission tomography imaging, maximun posterior (MAP) reconstruction can greatly improve the quality of reconstructed image by introducing prior distribution constraint. But a improper prior distribution may result in over-smoothess and stepladder edge of reconstructed image. OBJECTIVE: To put forward an algorithm combines with anisotropic diffusion filter and MAP improved by Thin Plate prior according to over-smoothess and stepladder edge of reconstructed image by traditional MAP with local prior information. METHODS: Reconstruction algorithm consists of anisotropic diffusion filter based on equation with forward-and-backward diffusion coefficient and MAP estimation based on Thin Plate prior. Reconstructed images were obtained by the alternate iteration of the above two steps. The quality of reconstructed images was evaluate by normalized rms error (RMSE) and signal-to-noise ratio (SNR). RESULTS AND CONCLUSION: Reconstructed images obtained by MAP with second-order second Thin Plate prior model combined with anisotropic diffusion filter based on forward-and-backward diffusion coefficient partial differential equation were improved in restrain noise, edge-preserving, SNR, RMSE, visual evaluation and so on.
作者 张权 刘祎
出处 《中国组织工程研究与临床康复》 CAS CSCD 北大核心 2011年第52期9797-9802,共6页 Journal of Clinical Rehabilitative Tissue Engineering Research
基金 山西省自然科学基金重点项目(2009011020-2) 山西省高等学校科技开发项目资助(20081024) 中北大学2008年校青年科学基金~~
  • 相关文献

参考文献4

二级参考文献34

  • 1顾国华,王虎帮,王文君,刘伟.基于模糊方向滤波的SAR图像增强与去噪[J].遥感技术与应用,2006,21(6):556-559. 被引量:1
  • 2Gong Xing (Dept. of Biomedical Engineering, Zhejiang University, Hangzhou 310027).A TRUST REGION METHOD FOR MICROWAVE TOMOGRAPHY[J].Journal of Electronics(China),2001,18(2):181-184. 被引量:1
  • 3张红英,彭启琮,吴亚东.数字破损图像的非线性各向异性扩散修补算法[J].计算机辅助设计与图形学学报,2006,18(10):1541-1546. 被引量:21
  • 4刘李鹂,高智勇,刘向明.基于小波分析的红外乳腺图像去噪与增强的实验研究[J].北京生物医学工程,2007,26(3):229-232. 被引量:3
  • 5Leung Chung-Chu, Chan Ka-Shing, Chan Hoi-Mei, et al. A New Approach for Image Enhancement Applied to Low-contrast- low-illumination IC and Document Images[J]. Pattern Recognition Letters, 2005, 26(6): 769-778.
  • 6Arici T, Dikbas S, Altunbasak Y. Local Contrast Enhancement Using 2-Dimensional Recursive Filters[C]//Proceedings of the 8^th IEEE Workshop on Multimedia Signal Processing. Victoria, Canada: IEEE Press, 2006: 329-333.
  • 7Rudin L, Osher S. Total Variation Based Image Restoration with Free Local Constraints[C]//Proceedings of the IEEE ICIP'94. Austin, TX, USA: IEEE Press, 1994: 31-35.
  • 8Denisova NV. Bayesian reconstruction in SPECT with entropy prior and iterative statistical regularization. IEEE Trans Nuclear Sci. 2004;51:136-141.
  • 9Lee NY, Choi Y. A modified OSEM algorithm for PET reconstruction using wavelet processing. Comp Methods Program Biom. 2005;80:236-245.
  • 10Shepp LA, Vardi Y. Maximum likelihood reconstruction for emission tomography. IEEE Trans Med Imaging. 1982;1(2): 113-122.

共引文献23

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