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. MAP-SIM can potentially reduce reconstruction artifacts, which commonly occur due to refractive index mismatch within the sample and to imperfections in the illumination. AVAILABILITY AND IMPLEMENTATION: SIMToolbox, example data and the online documentation are freely accessible at http://mmtg.fel.cvut.cz/SIMToolbox. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

We propose a novel binarization method based on a signal reconstruction using an iterative detection network. The algorithm simulates the whole image acquisition process taking into account a point spread function of the imaging system and its noise characteristics. The negative influence of image blur and noise is effectively suppressed by iterative detection network based on the criterion of maximum a posteriori probability. The proposed method was successfully applied to noisy microscopy images. Experiments show that the proposed method due to the noise suppression and deconvolution properties provides for noisy images significantly better results compared to common thresholding techniques. Binarized images obtained by the proposed method can be particularly useful for particle detection and analysis of cell samples.