SIMToolbox: a MATLAB toolbox for structured illumination fluorescence microscopy.

Unlabelled: SIMToolbox is an open-source, modular set of functions for MATLAB equipped with a user-friendly graphical interface and designed for processing two-dimensional and three-dimensional data acquired by structured illumination microscopy (SIM). Both optical sectioning and super-resolution applications are supported. The software is also capable of maximum a posteriori probability image estimation (MAP-SIM), an alternative method for reconstruction of structured illumination images.

High density 3D localization microscopy using sparse support recovery.

Single-molecule localization microscopy methods offer high spatial resolution, but they are not always suitable for live cell imaging due to limited temporal resolution. One strategy is to increase the density of photoactivated molecules present in each image, however suitable analysis algorithms for such data are still lacking. We present 3denseSTORM, a new algorithm for localization microscopy which is able to recover 2D or 3D super-resolution images from a sequence of diffraction limited images with high densities of photoactivated molecules.

Three-dimensional super-resolution structured illumination microscopy with maximum a posteriori probability image estimation.

We introduce and demonstrate a new high performance image reconstruction method for super-resolution structured illumination microscopy based on maximum a posteriori probability estimation (MAP-SIM). Imaging performance is demonstrated on a variety of fluorescent samples of different thickness, labeling density and noise levels. The method provides good suppression of out of focus light, improves spatial resolution, and allows reconstruction of both 2D and 3D images of cells even in the case of weak signals.

ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging.

Unlabelled: ThunderSTORM is an open-source, interactive and modular plug-in for ImageJ designed for automated processing, analysis and visualization of data acquired by single-molecule localization microscopy methods such as photo-activated localization microscopy and stochastic optical reconstruction microscopy. ThunderSTORM offers an extensive collection of processing and post-processing methods so that users can easily adapt the process of analysis to their data. ThunderSTORM also offers a set of tools for creation of simulated data and quantitative performance evaluation of localization algorithms using Monte Carlo simulations.

A benchmark for comparison of cell tracking algorithms.

Motivation: Automatic tracking of cells in multidimensional time-lapse fluorescence microscopy is an important task in many biomedical applications. A novel framework for objective evaluation of cell tracking algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2013 Cell Tracking Challenge. In this article, we present the logistics, datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark.

Flexible structured illumination microscope with a programmable illumination array.

Structured illumination microscopy (SIM) has grown into a family of methods which achieve optical sectioning, resolution beyond the Abbe limit, or a combination of both effects in optical microscopy. SIM techniques rely on illumination of a sample with patterns of light which must be shifted between each acquired image. The patterns are typically created with physical gratings or masks, and the final optically sectioned or high resolution image is obtained computationally after data acquisition.

Why has nature invented three stop codons of DNA and only one start codon?

We examine the standard genetic code with three stop codons. Assuming that the synchronization period of length 3 in DNA or RNA is violated during the transcription or translation processes, the probability of reading a frameshifted stop codon is higher than if the code would have only one stop codon. Consequently, the synthesis of RNA or proteins will soon terminate.

Minimizing detection errors in single molecule localization microscopy.

Fluorescence microscopy using single molecule imaging and localization (PALM, STORM, and similar approaches) has quickly been adopted as a convenient method for obtaining multicolor, 3D superresolution images of biological samples. Using an approach based on extensive Monte Carlo simulations, we examined the performance of various noise reducing filters required for the detection of candidate molecules. We determined a suitable noise reduction method and derived an optimal, nonlinear threshold which minimizes detection errors introduced by conventional algorithms.