3 research outputs found
Single-molecule localization microscopy analysis with ImageJ
ImageJ is a versatile and powerful tool for quantitative image analysis in microscopy. It is open-source software, platform-independent and enables students and researchers to obtain an easy but thorough introduction into image analysis. Especially the image processing package Fiji is a valuable and powerful extension of ImageJ. Several plugins and macros for single-molecule localization microscopy (SMLM) have been developed during the last decade. These novel tools cover the steps from single-molecule localization and image reconstruction to SMLM data postprocessing such as density analysis, image registration or resolution estimation. This article describes how ImageJ/Fiji can be used for image analysis, reviews existing extensions for SMLM, and aims at introducing and motivating novices and advanced SMLM users alike to explore the possibilities of ImageJ/Fiji for automated and quantitative data analysis
DeepCEL0 for 2D Single Molecule Localization in Fluorescence Microscopy
In fluorescence microscopy, Single Molecule Localization Microscopy (SMLM)
techniques aim at localizing with high precision high density fluorescent
molecules by stochastically activating and imaging small subsets of blinking
emitters. Super Resolution (SR) plays an important role in this field since it
allows to go beyond the intrinsic light diffraction limit. In this work, we
propose a deep learning-based algorithm for precise molecule localization of
high density frames acquired by SMLM techniques whose -based loss
function is regularized by positivity and -based constraints. The
is relaxed through its Continuous Exact (CEL0)
counterpart. The arising approach, named DeepCEL0, is parameter-free, more
flexible, faster and provides more precise molecule localization maps if
compared to the other state-of-the-art methods. We validate our approach on
both simulated and real fluorescence microscopy data