Structured illumination fluorescence microscopy using Talbot self-imaging effect for high-throughput visualization

TL;DR

This paper introduces a high-throughput structured illumination microscopy technique leveraging the Talbot self-imaging effect to generate large field-of-view, high-resolution patterns without being limited by the objective's numerical aperture.

Contribution

It presents a novel method combining Talbot self-imaging with structured illumination microscopy to achieve large FOV and sub-diffraction resolution simultaneously.

Findings

Achieved 500 nm resolution across a 450 x 350 um FOV.

Demonstrated a fourfold resolution improvement over diffraction limit.

Enabled high-throughput imaging with large FOV and super-resolution.

Abstract

We report a novel extension to structured illumination (SI) microscopy that utilizes the Talbot self-imaging effect to generate a SI pattern on a sample with field-of-view (FOV) and resolution unconstrained by the numerical aperture (NA) of the microscope objective. This enables high-resolution SI pattern generation (up to the free-space propagation limit) across large FOVs, which in turn allows SI microscopy to be efficiently adapted for high-throughput imaging. We demonstrated this concept using a simple prototype microscope to image a large FOV (450 x 350 um) with a diffraction-limited fluorescence resolution limited by the microscope NA to 2 um. A custom-fabricated structured element, designed with periodic spatial features beyond the diffraction limit of the microscope imaging objective, was positioned to within an integer multiple of half the Talbot distance away from the sample. This generated a large FOV, sub-diffraction SI pattern at the sample plane via the Talbot self-imaging effect. Conventional SI super-resolution principles were then used to increase imaging resolution to 500 nm across the complete FOV, roughly a factor of 4 improvement over the microscope NA diffraction limit. This approach should also be applicable for high-throughput sub-diffraction resolution multimodal imaging.