Bioimaging: Principles and Techniques

The formulation of the Finite-Difference Time-Domain (FDTD) approach is presented in the framework of its potential applications to in vivo flow cytometry based on light scattering. The consideration is focused on comparison of light scattering by a single biological cell alone in controlled refractive index matching conditions and by cells labeled by gold nanoparticles. The optical schematics including phase contrast (OPCM) microscopy as a prospective modality for in vivo flow cytometry is also analyzed. The validation of the FDTD approach for the simulation of flow cytometry may open a new avenue in the development of advanced cytometric techniques based on scattering effects from nanoscale targets.

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Light scattering effects of gold nanoparticles in cells: FDTD modeling

Tanev

Tuchin

Paddon

2006

Laser Phys. Lett.

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The FDTD modeling approach is applied to study the implementation of the optical immersion technique for the visualization of single and multiple gold nanoparticles in biological cells. To the best knowledge of authors, this is the first research study discussing the gold nanoparticle effects on the forward scattered light from biological cells at refractive index matching conditions. The applicability and the potential of the FDTD approach for studying gold nanoparticles enhanced bio-imaging at optical immersion is demonstrated.

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Bioimaging: Principles and Techniques

Cited by 20 publications

References 70 publications

Optical Imaging of Cells with Gold Nanoparticle Clusters as Light Scattering Contrast Agents: A Finite‐Difference Time‐Domain Approach to the Modeling of Flow Cytometry Configurations

Optical Imaging of Cells with Gold Nanoparticle Clusters as Light Scattering Contrast Agents: A Finite‐Difference Time‐Domain Approach to the Modeling of Flow Cytometry Configurations

Flow cytometry with gold nanoparticles and their clusters as scattering contrast agents: FDTD simulation of light–cell interaction

Light scattering effects of gold nanoparticles in cells: FDTD modeling

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