TestSTORM: Simulator for optimizing sample labeling and image acquisition in localization based super-resolution microscopy

Abstract

Localization-based super-resolution microscopy image quality depends on several factors such as dye choice and labeling strategy, microscope quality and user-defined parameters such as frame rate and number as well as the image processing algorithm. Experimental optimization of these parameters can be time-consuming and expensive so we present TestSTORM, a simulator that can be used to optimize these steps. TestSTORM users can select from among four different structures with specific patterns, dye and acquisition parameters. Example results are shown and the results of the vesicle pattern are compared with experimental data. Moreover, image stacks can be generated for further evaluation using localization algorithms, offering a tool for further software developments.

Local dimensionality determines imaging speed in localization microscopy

“…For example, on a line type structure the bias will be towards the centre of the line (see Sinkó et al 18. for a more detailed analysis).…”

“…Therefore, considerable effort has been put into evaluating localization microscopy algorithms and into finding fair ways to evaluate localization microscopy images. For the evaluation of algorithms, the most standard method has been to perform tests on simulations of a known ground truth structure and then test how well that structure is reproduced1218. Unfortunately, for real experiments ground truth is not available.…”

Origin and compensation of imaging artefacts in localization-based super-resolution microscopy

“…The position of the dye molecules were generated by means of the testSTORM [23,24] test pattern generator software. The PSFs of the molecules were calculated with the OSLO optical design software.…”

Leképezési és képrekonstrukciós hibák vizsgálata és korrekciója a nagyfeloldású lokalizációs mikroszkópiában

“…Therefore I studied how possible artifacts can occur and how an optimization can perform to determine an optimal process window in the parameter space for imaging in case of four types of sample geometry. [95] New scientific results…”

“…Therefore I created a software (TestSTORM) which models the whole imaging process in the localization based microscopy. [95] 4. The significance and quality of artifacts depends on the sample geometry and the imaging parameter such as labeling density, frame rate or pixel size.…”