Out-of-focus background subtraction for fast structured illumination super-resolution microscopy of optically thick samples

Improved resolution in 3D structured illumination microscopy using 3D model-based restoration with positivity-constraint

The performance of structured illumination microscopy (SIM) systems depends on the computational method used to process the raw data. In this paper, we present a regularized three-dimensional (3D) model-based (MB) restoration method with positivity constraint (PC) for 3D processing of data from 3D-SIM (or 3-beam interference SIM), in which the structured illumination pattern varies laterally and axially. The proposed 3D-MBPC method introduces positivity in the solution through the reconstruction of an auxiliary function using a conjugate-gradient method that minimizes the mean squared error between the data and the 3D imaging model. The 3D-MBPC method provides axial super resolution, which is not the same as improved optical sectioning demonstrated with model-based approaches based on the 2D-SIM (or 2-beam interference SIM) imaging model, for either 2D or 3D processing of a single plane from a 3D-SIM dataset. Results obtained with our 3D-MBPC method show improved 3D resolution over what is achieved by the standard generalized Wiener filter method, the first known method that performs 3D processing of 3D-SIM data. Noisy simulation results quantify the achieved 3D resolution, which is shown to match theoretical predictions. Experimental verification of the 3D-MBPC method with biological data demonstrates successful application to data volumes of different sizes.

Rapid Image Reconstruction of Structured Illumination Microscopy Directly in the Spatial Domain

Super-resolution structured illumination microscopy (SIM) routinely performs image reconstruction in the frequency domain using an approach termed frequency-domain reconstruction (FDR). Due to multiple Fourier transforms between the spatial and frequency domains, SIM suffers from low reconstruction speed, constraining its applications in real-time, dynamic imaging. To overcome this limitation, we developed a new method for SIM image reconstruction, termed spatial domain reconstruction (SDR). SDR is intrinsically simpler than FDR, does not require Fourier transforms and the theory predicts it to be a rapid image reconstruction method. Results show that SDR reconstructs a super-resolution image 7-fold faster than FDR, producing images that are equal to either FDR or the widely-used FairSIM. We provide a proof-of-principle using mobile fluorescent beads to demonstrate the utility of SDR in imaging moving objects. Consequently, replacement of the FDR approach with SDR significantly enhances SIM as the desired method for live-cell, instant super-resolution imaging. This means that SDR-SIM is a "What You See Is What You Get" approach to super-resolution imaging.

Tunable-frequency three-dimensional structured illumination microscopy with reduced data-acquisition

The performance of a tunable three-dimensional (3D) structured illumination microscope (SIM) system and its ability to provide simultaneously super-resolution (SR) and optical-sectioning (OS) capabilities are investigated. Numerical results show that the performance of our 3D-SIM system is comparable with the one provided by a three-wave interference SIM, while requiring 40% fewer images for the reconstruction and providing frequency tunability in a cost-effective implementation. The performance of the system has been validated experimentally with images from test samples, which were also imaged with a commercial SIM based on incoherent-grid projection for comparison. Restored images from data acquired from an axially-thin fluorescent layer show a 1.6× improvement in OS capability compared to the commercial instrument while results from a fluorescent tilted USAF target show the OS and SR capabilities achieved by our system.