
Modeling the depth-sectioning effect in reflection-mode dynamic speckle-field interferometric microscopy
Author(s) -
Renjie Zhou,
Di Jin,
Poorya Hosseini,
Vijay Raj Singh,
Yang-Hyo Kim,
Cuifang Kuang,
Ramachandra R. Dasari,
Zahid Yaqoob,
Peter T. C. So
Publication year - 2017
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.25.000130
Subject(s) - optics , speckle pattern , speckle imaging , optical coherence tomography , microscopy , optical sectioning , reflection (computer programming) , diffraction , coherence (philosophical gambling strategy) , interferometry , numerical aperture , image resolution , resolution (logic) , materials science , physics , computer science , artificial intelligence , wavelength , quantum mechanics , programming language
Unlike most optical coherence microscopy (OCM) systems, dynamic speckle-field interferometric microscopy (DSIM) achieves depth sectioning through the spatial-coherence gating effect. Under high numerical aperture (NA) speckle-field illumination, our previous experiments have demonstrated less than 1 μm depth resolution in reflection-mode DSIM, while doubling the diffraction limited resolution as under structured illumination. However, there has not been a physical model to rigorously describe the speckle imaging process, in particular explaining the sectioning effect under high illumination and imaging NA settings in DSIM. In this paper, we develop such a model based on the diffraction tomography theory and the speckle statistics. Using this model, we calculate the system response function, which is used to further obtain the depth resolution limit in reflection-mode DSIM. Theoretically calculated depth resolution limit is in an excellent agreement with experiment results. We envision that our physical model will not only help in understanding the imaging process in DSIM, but also enable better designing such systems for depth-resolved measurements in biological cells and tissues.