Linear Phase Recovery From DIC Microscope

Physics

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Coherence, Light Propagation, Cellular Biophysics, Polarization, Image Reconstruction, Coherence, Electromagnetic Wave Propagation, Radiowave Propagation, Cell Adhesion And Cell Mechanics, Scattering, Polarization, Image Reconstruction, Tomography

Scientific paper

Phase contrast imaging is a specific technique in optical microscopy that is able to capture the minute structures of unlabeled biological sample from contrast generated in the variations of the object's refractive index. It is especially suitable for living cells and organisms that are hardly visible under conventional light microscopy as they barely alter the intensity and only introduce phase shifts in the transmitted light. Optical phase imaging has great potential in biomedical applications from examining both topological and three-dimensional biophysical properties of biological specimens. Conventional DIC microscopy with partially coherent light source is a very powerful technique for phase contrast imaging with its pseudo 3D bias-relief look, and is able to yield higher lateral resolution compared to other interferometric phase imaging methods. Most importantly, DIC microscope generates contrast from within the sample's own intrinsic properties and is the preferred tool for visualization in most biology laboratories after fluorescence. However, it is inherently qualitative and the information obtained is a phase-gradient image rather than a true linear mapping of the optical path length (OPL) differences. We propose a novel method here that extends the Transport-of-Intensity Equation (TIE) and combines the correlation of light intensity and phase with polarization-modulated differential interference contrast (DIC) microscopy. Numerically solving the relationship of light propagation in a series of through-focus DIC images allows linear phase information to be completely determined and restored from phase gradients in two-dimensional planes. Since the computation is deterministic, live time imaging of cellular dynamics can be obtained with superior resolution without much hardware modification or additional computation complexity.

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