Fast live cell imaging at nanometer scale using annihilating filter based low rank Hankel matrix approach

Lina Carlini, Suliana Manley, Michaël Unser
Spie-Int Soc Optical Engineering, 2015
Conference paper

Abstract

Localization microscopy such as STORM/PALM can achieve a nanometer scale spatial resolution by iteratively localizing fluorescence molecules. It was shown that imaging of densely activated molecules can accelerate temporal resolution which was considered as major limitation of localization microscopy. However, this higher density imaging needs to incorporate advanced localization algorithms to deal with overlapping point spread functions (PSFs). In order to address this technical challenges, previously we developed a localization algorithm called FALCON1, 2 using a quasi-continuous localization model with sparsity prior on image space. It was demonstrated in both 2D/3D live cell imaging. However, it has several disadvantages to be further improved. Here, we proposed a new localization algorithm using annihilating filter-based low rank Hankel structured matrix approach (ALOHA). According to ALOHA principle, sparsity in image domain implies the existence of rankdeficient Hankel structured matrix in Fourier space. Thanks to this fundamental duality, our new algorithm can perform data-adaptive PSF estimation and deconvolution of Fourier spectrum, followed by truly grid-free localization using spectral estimation technique. Furthermore, all these optimizations are conducted on Fourier space only. We validated the performance of the new method with numerical experiments and live cell imaging experiment. The results confirmed that it has the higher localization performances in both experiments in terms of accuracy and detection rate.

Official source

https://infoscience.epfl.ch/record/216149?ln=en

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related concepts

Related publications

Lina Carlini, Suliana Manley, Michaël Unser
Spie-Int Soc Optical Engineering, 2015
Conference paper

Abstract

Official source

https://infoscience.epfl.ch/record/216149?ln=en

About this result

Related concepts (18)

Related concepts

Related publications (25)

Related publications

, , ,

Localization microscopy achieves nanoscale spatial resolution by iterative localization of sparsely activated molecules, which generally leads to a long acquisition time. By implementing advanced algorithms to treat overlapping point spread functions (PSFs), imaging of densely activated molecules can improve the limited temporal resolution, as has been well demonstrated in two-dimensional imaging. However, three-dimensional (3D) localization of high-density data remains challenging since PSFs are far more similar along the axial dimension than the lateral dimensions. Here, we present a new, high-density 3D imaging system and algorithm. The hybrid system is implemented by combining astigmatic and biplane imaging. The proposed 3D reconstruction algorithm is extended from our state-of-the art 2D high-density localization algorithm. Using mutual coherence analysis of model PSFs, we validated that the hybrid system is more suitable than astigmatic or biplane imaging alone for 3D localization of high-density data. The efficacy of the proposed method was confirmed via simulation and real data of microtubules. Furthermore, we also successfully demonstrated fluorescent-protein-based live cell 3D localization microscopy with a temporal resolution of just 3 seconds, capturing fast dynamics of the endoplasmic recticulum. (C) 2014 Optical Society of America

Optical Soc Amer2014

Waveguide platform and methods for super-resolution fluorescence microscopy of sub-cellular structures

Anna Archetti

Super-resolution fluorescence microscopy is widespread, owing to its demonstrated ability to resolve dynamical processes within cells and to identify the structure and position of specific proteins in the interior of protein complexes. Nowadays, subcellular features can be routinely resolved at the nanoscopic scale thanks to the accessibility of straightforward sample-preparation protocols, simple hardware tools, and open source software. Building on its ability to investigate large-scale macromolecules networks in their natural environment with high resolution, fluorescence microscopy is further evolving by the development of quantitative and high-throughput methods to characterize such networks. Previous implementations of high-throughput microscopy made use of imaging sequentially smaller fields of view (FOV), which makes axial alignment a challenge and extends the imaging time. In our work, we circumvent these problems with our large FOV systems, which are based on flat-field sample illumination over large areas, combined with a CMOS-camera. In this thesis, I present a waveguide platform designed to image a wide area with low background by mean of total internal reflection fluorescence (TIRF) excitation. The waveguide chips for this platform were fabricated at the center of micro-nano technology (CMi) at EPFL, in collaboration with the group of Aleksandra Radenovic (specifically with Evgenii Glushkov). The resulting waveguide-TIRF system is specifically optimized for applications where easy and repetitive buffer exchange is needed. To achieve large and uniform TIRF excitation, I studied some fundamental parameters of the waveguide, developing specific code to simulate, at the first order, its behavior. I then extended light propagation solutions adopted in the field of integrated photonics to our waveguide chip fabrication process. To easily integrate the chip within the commercial stage of an upright microscope, I designed a novel chip holder that ensures aqueous solution sealing, mitigates the presence of scatter light in the imaging area, and facilitates the waveguide alignment during the input beam-coupling phase. On the analysis side, the need for computational tools that are specific to fluorescence microscopy is continuously growing, due to the fact that this technique heavily relies on the treatment of large quantities of data. The automated analysis of images is a fundamental step of the measurement process, necessary for unbiased quantification and statistical validation, especially where repetitive visual inspection would be impractically long. This is particularly critical for single molecule localization microscopy (SMLM), where the quality of the reconstructed super-resolved image actually is a trade-off between the algorithm localization precision and its speed, a key element considering the need of processing tens of thousands of large images to generate the final, super-resolved one. In this work, I present a series of computational tools for CMOS camera characterization developed for large flat-field STORM microscopy, a 3D SMLM reconstruction software specific for Double-Helix (DH) point spread function (PSF) and a set of cell shape analysis tools to study C.Crescentus shape dynamics.

EPFL2019

This thesis introduces a collection of physics-based methods for super-resolution in optical microscopy. The core of these methods constitutes a framework for 3-D localization of single fluorescent molecules. Localization is formulated as a parameter estimation problem relying on a physically accurate model of the system's point spread function (PSF). In a similar approach, methods for fitting PSF models to experimental observations and for extended-depth-of-field imaging are proposed. Imaging of individual fluorophores within densely labeled samples has become possible with the discovery of dyes that can be photo-activated or switched between fluorescent and dark states. A fluorophore can be localized from its image with nanometer-scale accuracy, through fitting with an appropriate image function. This concept forms the basis of fluorescence localization microscopy (FLM) techniques such as photo-activated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), which rely on Gaussian fitting to perform the localization. Whereas the image generated by a single fluorophore corresponds to a section of the microscope's point spread function, only the in-focus section of the latter is well approximated by a Gaussian. Consequently, applications of FLM have for the most part been limited to 2-D imaging of thin specimen layers. In the first section of the thesis, it is shown that localization can be extended to 3-D without loss in accuracy by relying on a physically accurate image formation model in place of a Gaussian approximation. A key aspect of physically realistic models lies in their incorporation of aberrations that arise either as a consequence of mismatched refractive indices between the layers of the sample setup, or as an effect of experimental settings that deviate from the design conditions of the system. Under typical experimental conditions, these aberrations change as a function of sample depth, inducing axial shift-variance in the PSF. This property is exploited in a maximum-likelihood framework for 3-D localization of single fluorophores. Due to the shift-variance of the PSF, the axial position of a fluorophore is uniquely encoded in its diffraction pattern, and can be estimated from a single acquisition with nanometer-scale accuracy. Fluroescent molecules that remain fixed during image acquisition produce a diffraction pattern that is highly characteristic of the orientation of the fluorophore's underlying electromagnetic dipole. The localization is thus extended to incorporate the estimation of this 3-D orientation. It is shown that image formation for dipoles can be represented through a combination of six functions, based on which a 3-D steerable filter for orientation estimation and localization is derived. Experimental results demonstrate the feasibility of joint position and orientation estimation with accuracies of the order of one nanometer and one degree, respectively. Theoretical limits on localization accuracy for these methods are established in a statistical analysis based on Cramér-Rao bounds. A noise model for fluorescence microscopy based on a shifted Poisson distribution is proposed. In these localization methods, the aberration parameters of the PSF are assumed to be known. However, state-of-the-art PSF models depend on a large number of parameters that are generally difficult to determine experimentally with sufficient accuracy, which may limit their use in localization and deconvolution applications. A fitting algorithm analogous to localization is proposed; it is based on a simplified PSF model and shown to accurately reproduce the behavior of shift-variant experimental PSFs. Finally, it is shown that these algorithms can be adapted to more complex experiments, such as imaging of thick samples in brightfield microscopy. An extended-depth-of-field algorithm for the fusion of in-focus information from frames acquired at different focal positions is presented; it relies on a spline representation of the sample surface and as a result yields a continuous and super-resolved topography of the specimen.

EPFL2009

Waveguide platform and methods for super-resolution fluorescence microscopy of sub-cellular structures

Anna Archetti

EPFL2019

EPFL2009