Three dimensional drift control at nano-scale in single molecule localization microscopy

ResNet-based image inpainting method for enhancing the imaging speed of single molecule localization microscopy

Single molecule localization microscopy (SMLM) is a mainstream method in the field of super-resolution fluorescence microscopy that can achieve a spatial resolution of 20∼30 nm through a simple optical system. SMLM usually requires thousands of raw images to reconstruct a super-resolution image, and thus suffers from a slow imaging speed. Recently, several methods based on image inpainting have been developed to enhance the imaging speed of SMLM. However, these image inpainting methods may also produce erroneous local features (or called image artifacts), for example, incorrectly joined or split filaments. In this study, we use the ResNet generator, a network with strong local feature extraction capability, to replace the popularly-used U-Net generator to minimize the image artifact problem in current image inpainting methods, and develop an image inpainting method called DI-STORM. We validate our method using both simulated and experimental data, and demonstrate that DI-STORM has the best acceleration capability and produces the least artifacts in the repaired images, as compared with VDSR (the simplest CNN-based image inpainting method in SMLM) and ANNA-PALM (the best GAN-based image inpainting method in SMLM). We believe that DI-STORM could facilitate the application of deep learning-based image inpainting methods for SMLM.

Influence of drift correction precision on super-resolution localization microscopy

Super-resolution localization microscopy (SRLM) breaks the diffraction limit successfully and improves the resolution of optical imaging systems by nearly an order of magnitude. However, SRLM typically takes several minutes or longer to collect a sufficient number of image frames that are required for reconstructing a final super-resolution image. During this long image acquisition period, system drift should be tightly controlled to ensure the imaging quality; thus, several drift correction methods have been developed. However, it is still unclear whether the performance of these methods is able to ensure sufficient image quality in SRLM. Without a clear answer to this question, it is hard to choose a suitable drift correction method for a specific SRLM experiment. In this paper, we use both theoretical analysis and simulation to investigate the relationship among drift correction precision, localization precision, and position estimation precision. We propose a concept of relative localization precision for evaluating the effect of drift correction on imaging resolution, which would help to select an appropriate drift correction method for a specific experiment.

Robust, fiducial-free drift correction for super-resolution imaging

We describe a robust, fiducial-free method of drift correction for use in single molecule localization-based super-resolution methods. The method combines periodic 3D registration of the sample using brightfield images with a fast post-processing algorithm that corrects residual registration errors and drift between registration events. The method is robust to low numbers of collected localizations, requires no specialized hardware, and provides stability and drift correction for an indefinite time period.

High-precision 3D drift correction with differential phase contrast images

Single molecule localization microscopy (SMLM) usually requires long image acquisition time at the order of minutes and thus suffers from sample drift, which deteriorates image quality. A drift estimation method with high precision is typically used in SMLM, which can be further combined with a drift compensation device to enable active microscope stabilization. Among all the reported methods, the drift estimation method based on bright-field image correlation requires no extra sample preparation or complicated modification to the imaging setup. However, the performance of this method is limited by the contrast of bright-field images, especially for the structures without sufficient features. In this paper, we proposed to use differential phase contrast (DPC) microscopy to enhance the image contrast and presented a 3D drift correction method with higher precision and robustness. This DPC-based drift correction method is suitable even for biological samples without clear morphological features. We demonstrated that this method can achieve a correction precision of < 6 nm in both the lateral direction and axial direction. Using SMLM imaging of microtubules, we verified that this method provides a comparable drift estimation performance as redundant cross-correlation.

Simple way to correct the drift in surface-coupled optical tweezers using the laser reflection pattern

The surface-coupled optical tweezers are widely used to resolve small units of motion in biology. However, such motions could readily be interfered by the drift between the trap and surface. We present a simple and low-cost method to correct the drift both actively and passively based on video tracking the distance between the laser reflection pattern and the reference bead. As a result, we achieved sub-nanometer resolution and stability for the stuck bead over a broad range of averaging time (0.002-100 s) as demonstrated by the Allan deviation analysis. The sub-nanometer resolution was further manifested with step measurement. Finally, in double-stranded DNA and DNA hairpin stretching experiments, an extension resolution of 1-2 nm with the stability over 120 s has been demonstrated under a constant force. This work thus provides an easy way to bring the benefit of nanometer resolution and long-term stability to the surface-coupled optical tweezers.