Haldar Justin P, Wang Zhuo, Popescu Gabriel, Liang Zhi-Pei
Department of Electrical and Computer Engineering and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:3382-5. doi: 10.1109/IEMBS.2010.5627917.
Spatial light interference microscopy (SLIM) is a powerful new quantitative phase optical imaging technique that can be used for studying live cells without the need for exogenous contrast agents. This paper proposes a novel deconvolution-based approach to reconstructing SLIM data, which dramatically improves the visual quality of the images. The proposed deconvolution formulation is tailored to the physics of SLIM imaging of biological samples, and a new fast algorithm is designed for computationally-efficient image reconstruction in this setting. Simulation and experimental results demonstrate that deconvolution can reduce the width of the point-spread function by at least 20%, and can significantly improve the contrast of high-resolution features. Temporally-resolved SLIM imaging with the high spatial resolution enabled by deconvolution provides new opportunities for studying the dynamics of cellular and sub-cellular processes.
空间光干涉显微镜（SLIM）是一种强大的新型定量相位光学成像技术，可用于研究活细胞，无需外源性造影剂。本文提出了一种基于反卷积的新颖方法来重建SLIM数据，这显著提高了图像的视觉质量。所提出的反卷积公式是根据生物样品SLIM成像的物理原理定制的，并设计了一种新的快速算法，以便在这种情况下进行计算高效的图像重建。仿真和实验结果表明，反卷积可以将点扩散函数的宽度至少减小20%，并能显著提高高分辨率特征的对比度。通过反卷积实现的高空间分辨率的时间分辨SLIM成像为研究细胞和亚细胞过程的动力学提供了新的机会。
