期刊文献+

应用共焦空间微分显微镜获取边缘增强显微图像 被引量:7

Application of Spatial Differential Confocal Microscopy in Obtaining Edge Enhanced Microscopic Images
原文传递
导出
摘要 生物样品图像边缘增强与提取是医学图像处理的关键技术之一,是进行生物样品形态分析的基础。图像边缘增强通常是通过计算机编程对原始图像进行后期处理来实现的,然而,这里应用共焦空间微分显微镜系统,实现了在获得样品共焦显微图像的同时直接获取对应的边缘增强显微图像,且图像分辨率与对比度较高。实验不仅获取了掩膜板与标准分辨率板RTA-07的边缘增强图像,说明系统分辨率达到1.5μm,而且实现了生物细胞的边缘增强图像的获取,如血红细胞与口腔上皮细胞,图像可用于样品尺度与面积等形态的分析与计算,在生物医学研究中有实际应用意义。 Edge enhancement and extraction of biological samples' images are one of the key technologies for the processing of medical images, and the basis of samples' morphological analysis. In general, the realization for image edge enhancement is through post processing of original images by computer programming. However, spatial differential confocal microscopy system has been applied to directly obtain the high resolution and contrast edge enhanced microscopic images of samples while the confocal microscopic images are obtained. The biomedical application is demonstrated not only for edge enhancement imaging for a mask and a resolution test target (RTA-07) that shows the resolution of the system is 1.5 /~m, but also for edge enhancement imaging for biological cells like RBCs and oral epithelial cells. The obtained edge enhanced microscopic images can be used for simply sample morphological analysis and calculation, such as the scale and area, which has a practical application significance in the research of biomedicine.
出处 《光学学报》 EI CAS CSCD 北大核心 2014年第3期209-213,共5页 Acta Optica Sinica
基金 国家自然科学基金(61178086) 广东省自然科学基金重点项目(S2013020012810)
关键词 图像处理 共焦显微镜 边缘增强图像 空间微分技术 细胞 形态分析 image processing confocal microscopy edge enhanced images spatial differential technique cells morphological analysis
  • 相关文献

参考文献5

二级参考文献52

  • 1王治华,俞信.液晶空间光调制器相位调制测量及波前校正[J].光学技术,2005,31(2):196-199. 被引量:13
  • 2钟可君,唐志列,陈更生,卢非,李凌燕.一种实现光声光谱的导数光谱的新方法[J].光学学报,2005,25(9):1288-1292. 被引量:3
  • 3闫成新,桑农,张天序.基于图论的图像分割研究进展[J].计算机工程与应用,2006,42(5):11-14. 被引量:33
  • 4王彩芳,姜明.医学图像配准综述[J].CT理论与应用研究(中英文),2006,15(2):74-80. 被引量:4
  • 51T.Wilson.Confocal Microscopy[M].New York:AcademicPress,1990.
  • 6Pascale Guitera,Giovanani Pellacani,Kerry A.Crotty et al..The impact of in vivo reflectance confocal microscopy on thediagnostic accuracy of lentigo maligna and equivocal pigmentedand nonpigmented macules of the face[J].J.InvestigativeDermatology,2010,130(8):2080-2091.
  • 7C.H.Lee,J.P.Wang.Noninterferometric differential confocalmicroscopy with 2-nm depth resolution[J].Opt.Commun.,1997,35(2):233-237.
  • 8Lisong Yang,Li Liu,Guiying Wang et al..Noninterferometricmeasurement of lead zirconate titanate inverse piezoelectricextension[J].Opt.Engng.,2001,40(6):909-913.
  • 9Jiubin Tan,Jie Zhang.Differential confocal optical system usinggradient-index lenses[J].Opt.Engng.,2003,42(10):2868-2871.
  • 10C.J.R.Sheppaed,C.J.Cogswell.Image formation in video-enhanced and confocal DIC microscopy[C].SPIE,1994,1846:64-71.

共引文献62

同被引文献58

  • 1王良诚,赵建文,赵晶.连续变倍体视显微镜的设计及性能扩展[J].光学仪器,1996,18(1):6-12. 被引量:1
  • 2谢风英,赵丹培.VisualC++数字图像处理[M].北京:电子工业出版社,2008.
  • 3C H Ooi, N A M Isa. Quadrants dynamic histogram equalization for contrast enhancement [J]. IEEE Transactions on Consumer Electronics, 2010, 56(4): 2552-2559.
  • 4T Iwanami, T Goto, S Hirano, et al. An adaptive contrast enhancement using regional dynamic histogram equalization[J]. IEEE International Conference on Consumer Electronics, 2012. 719-722.
  • 5) T Celik, T Tjahjadi. Automatic image equalization and contrast enhancement using Gaussian mixture modeling [J ]. IEEE Transactions on Image Processing, 2012, 21(1): 145-156.
  • 6M Figueiredo, A Jain. Unsupervised learning of finite mixture models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(3): 381-396.
  • 7D Menotti, L Najman, J Facon, et al. Multi-histogram equalization methods for contrast enhancement and brightness preserving[J]. IEEE Transactions on Consumer Electronics, 2007, 53(3) : 1186-1194.
  • 8Homem M R P, Mascarenhas N D A, da Costa L F. Linear filters for deconvolution microscopy[C]. 6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004: 142-146.
  • 9Laksameethanasan D, Brandt S S, Engelhardt P. A three-dimensional Bayesian reconstruction method with the point spread function for micro-rotation sequences in wide-field microscopy[C]. 3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006: 1276-1279.
  • 10Soulez F, Denis L, Tourneur Y, et al.. Blind deconvolution of 3D data in wide field fluorescence microscopy[C]. 9th IEEE International Symposium on Biomedical Imaging (ISBI), 2012: 1735-1738.

引证文献7

二级引证文献25

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