Sub-pixel deconvolution of 3D optical microscope imagery

被引:3
作者
Biggs, DSC [1 ]
Wang, CL [1 ]
Holmes, TJ [1 ]
Khodjakov, A [1 ]
机构
[1] AutoQuant Imaging Inc, Watervliet, NY 12189 USA
来源
ADVANCED SIGNAL PROCESSING ALGORITHMS, ARCHITECTURES, AND IMPLEMENTATIONS XIV | 2004年 / 5559卷
关键词
deconvolution; super-resolution; sub-pixel; 3D microscopy; iterative algorithms; point spread function;
D O I
10.1117/12.559526
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Optical light microscopy is a predominant modality for imaging living cells. with the maximum resolution typically diffraction limited to approximately 200nm. The objective of this project is to enhance the resolution capabilities of optical light microscopes using image-processing algorithms. to produce super-resolved imagery at a sub-pixel level. The sub-pixel algorithm is based on maximum-likelihood iterative deconvolution of photon-limited data. and reconstructs the image at a finer scale than the pixel limitation of the camera. The software enhances the versatility of light microscopes, and enables the observation of sub-cellular components at a resolution two to three times finer than previously. Adaptive blind deconvolution is used to automatically determine the point spread function from the observed data. The technology also allows camera-binned or sub-sampled (aliased) data to be correctly processed. Initial investigations used computer simulations and 3D imagery from widefield epi-fluorescence light microscopy.
引用
收藏
页码:369 / 380
页数:12
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