A literature review of localization methods and emergence of deep learning in single-molecule localization microscopy

2020 ◽  
Author(s):  
Anish Mukherjee
Keyword(s):  
Deep Learning ◽  
Single Molecule ◽  
Super Resolution ◽  
Point Sources ◽  
Learning Approaches ◽  
Localization Algorithm ◽  
Localization Microscopy ◽  
Trade Offs ◽  
Emitter Localization ◽  
Single Molecule Localization Microscopy

The quality of super-resolution images largely depends on the performance of the emitter localization algorithm used to localize point sources. In this article, an overview of the various techniques which are used to localize point sources in single-molecule localization microscopy are discussed and their performances are compared. This overview can help readers to select a localization technique for their application. Also, an overview is presented about the emergence of deep learning methods that are becoming popular in various stages of single-molecule localization microscopy. The state of the art deep learning approaches are compared to the traditional approaches and the trade-offs of selecting an algorithm for localization are discussed.

scholarly journals Analyzing Single Molecule Localization Microscopy Data Using Cubic Splines

2016 ◽  
Author(s):  
Hazen P. Babcock ◽  
Xiaowei Zhuang
Keyword(s):  
Single Molecule ◽  
Super Resolution ◽  
Computation Time ◽  
Cubic Splines ◽  
Localization Algorithm ◽  
Localization Microscopy ◽  
Analytical Functions ◽  
Open Source Software Package ◽  
Microscopy Data ◽  
Single Molecule Localization Microscopy

AbstractThe resolution of super-resolution microscopy based on single molecule localization is in part determined by the accuracy of the localization algorithm. In most published approaches to date this localization is done by fitting an analytical function that approximates the point spread function (PSF) of the microscope. However, particularly for localization in 3D, analytical functions such as a Gaussian, which are computationally inexpensive, may not accurately capture the PSF shape leading to reduced fitting accuracy. On the other hand, analytical functions that can accurately capture the PSF shape, such as those based on pupil functions, can be computationally expensive. Here we investigate the use of cubic splines as an alternative fitting approach. We demonstrate that cubic splines can capture the shape of any PSF with high accuracy and that they can be used for fitting the PSF with only a 2-3x increase in computation time as compared to Gaussian fitting. We provide an open-source software package that measures the PSF of any microscope and uses the measured PSF to perform 3D single molecule localization microscopy analysis with reasonable accuracy and speed.

scholarly journals Three-Dimensional Single-Molecule Localization Microscopy in Whole-Cell and Tissue Specimens

2020 ◽  
Vol 22 (1) ◽  
pp. 155-184 ◽  
Author(s):  
Sheng Liu ◽  
Hyun Huh ◽  
Sang-Hyuk Lee ◽  
Fang Huang
Keyword(s):  
Single Molecule ◽  
Three Dimensional ◽  
Super Resolution ◽  
Three Dimensions ◽  
Whole Cell ◽  
Localization Microscopy ◽  
Trade Offs ◽  
Protein Functions ◽  
Tissue Specimens ◽  
Single Molecule Localization Microscopy

Super-resolution microscopy techniques are versatile and powerful tools for visualizing organelle structures, interactions, and protein functions in biomedical research. However, whole-cell and tissue specimens challenge the achievable resolution and depth of nanoscopy methods. We focus on three-dimensional single-molecule localization microscopy and review some of the major roadblocks and developing solutions to resolving thick volumes of cells and tissues at the nanoscale in three dimensions. These challenges include background fluorescence, system- and sample-induced aberrations, and information carried by photons, as well as drift correction, volume reconstruction, and photobleaching mitigation. We also highlight examples of innovations that have demonstrated significant breakthroughs in addressing the abovementioned challenges together with their core concepts as well as their trade-offs.

scholarly journals Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software

2019 ◽  
Vol 16 (5) ◽  
pp. 387-395 ◽  
Author(s):  
Daniel Sage ◽  
Thanh-An Pham ◽  
Hazen Babcock ◽  
Tomas Lukes ◽  
Thomas Pengo ◽  
...  
Keyword(s):  
Single Molecule ◽  
Super Resolution ◽  
Localization Microscopy ◽  
Fight Club ◽  
2D And 3D ◽  
Single Molecule Localization Microscopy

scholarly journals Survey of Deep-Learning Approaches for Remote Sensing Observation Enhancement

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3929 ◽  
Author(s):  
Grigorios Tsagkatakis ◽  
Anastasia Aidini ◽  
Konstantina Fotiadou ◽  
Michalis Giannopoulos ◽  
Anastasia Pentari ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Deep Learning ◽  
Large Body ◽  
Super Resolution ◽  
Imaging Systems ◽  
Learning Approaches ◽  
Language Understanding ◽  
Learning Tasks ◽  
Trade Offs ◽  
Sensing Platforms

Deep Learning, and Deep Neural Networks in particular, have established themselves as the new norm in signal and data processing, achieving state-of-the-art performance in image, audio, and natural language understanding. In remote sensing, a large body of research has been devoted to the application of deep learning for typical supervised learning tasks such as classification. Less yet equally important effort has also been allocated to addressing the challenges associated with the enhancement of low-quality observations from remote sensing platforms. Addressing such channels is of paramount importance, both in itself, since high-altitude imaging, environmental conditions, and imaging systems trade-offs lead to low-quality observation, as well as to facilitate subsequent analysis, such as classification and detection. In this paper, we provide a comprehensive review of deep-learning methods for the enhancement of remote sensing observations, focusing on critical tasks including single and multi-band super-resolution, denoising, restoration, pan-sharpening, and fusion, among others. In addition to the detailed analysis and comparison of recently presented approaches, different research avenues which could be explored in the future are also discussed.

scholarly journals Super-resolution fight club: A broad assessment of 2D & 3D single-molecule localization microscopy software

2018 ◽  
Author(s):  
Daniel Sage ◽  
Thanh-An Pham ◽  
Hazen Babcock ◽  
Tomas Lukes ◽  
Thomas Pengo ◽  
...  
Keyword(s):  
Single Molecule ◽  
Double Helix ◽  
Super Resolution ◽  
Large Set ◽  
Holistic View ◽  
Localization Microscopy ◽  
Fight Club ◽  
Community Effort ◽  
2D And 3D ◽  
Single Molecule Localization Microscopy

ABSTRACTWith the widespread uptake of 2D and 3D single molecule localization microscopy, a large set of different data analysis packages have been developed to generate super-resolution images. To guide researchers on the optimal analytical software for their experiments, we have designed, in a large community effort, a competition to extensively characterise and rank these options. We generated realistic simulated datasets for popular imaging modalities – 2D, astigmatic 3D, biplane 3D, and double helix 3D – and evaluated 36 participant packages against these data. This provides the first broad assessment of 3D single molecule localization microscopy software, provides a holistic view of how the latest 2D and 3D single molecule localization software perform in realistic conditions, and ultimately provides insight into the current limits of the field.

scholarly journals Molecular resolution imaging by post-labeling expansion single-molecule localization microscopy (Ex-SMLM)

2020 ◽  
Author(s):  
Fabian U. Zwettler ◽  
Sebastian Reinhard ◽  
Davide Gambarotto ◽  
Toby D. M. Bell ◽  
Virginie Hamel ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Single Molecule ◽  
Super Resolution ◽  
Reference Structure ◽  
Positional Error ◽  
Localization Microscopy ◽  
Resolution Imaging ◽  
Endogenous Proteins ◽  
Super Resolution Microscopy ◽  
Single Molecule Localization Microscopy

AbstractExpansion microscopy (ExM) enables super-resolution fluorescence imaging of physically expanded biological samples with conventional microscopes. By combining expansion microscopy (ExM) with single-molecule localization microscopy (SMLM) it is potentially possible to approach the resolution of electron microscopy. However, current attempts to combine both methods remained challenging because of protein and fluorophore loss during digestion or denaturation, gelation, and the incompatibility of expanded polyelectrolyte hydrogels with photoswitching buffers. Here we show that re-embedding of expanded hydrogels enables dSTORM imaging of expanded samples and demonstrate that post-labeling ExM resolves the current limitations of super-resolution microscopy. Using microtubules as a reference structure and centrioles, we demonstrate that post-labeling Ex-SMLM preserves ultrastructural details, improves the labeling efficiency and reduces the positional error arising from linking fluorophores into the gel thus paving the way for super-resolution imaging of immunolabeled endogenous proteins with true molecular resolution.

scholarly journals Systematic Tuning of Rhodamine Spirocyclization for Super-Resolution Microscopy

2021 ◽  
Author(s):  
Nicolas Lardon ◽  
Lu Wang ◽  
Aline Tschanz ◽  
Philipp Hoess ◽  
Mai Tran ◽  
...  
Keyword(s):  
Single Molecule ◽  
Large Range ◽  
Dynamic Equilibrium ◽  
Super Resolution ◽  
Live Cell ◽  
Stimulated Emission ◽  
Important Class ◽  
Localization Microscopy ◽  
Super Resolution Microscopy ◽  
Single Molecule Localization Microscopy

Rhodamines are the most important class of fluorophores for applications in live-cell fluorescence microscopy. This is mainly because rhodamines exist in a dynamic equilibrium between a fluorescent zwitterion and a non-fluorescent but cell-permeable spirocyclic form. Different imaging applications require different positions of this dynamic equilibrium, which poses a challenge for the design of suitable probes. We describe here how the conversion of the ortho-carboxy moiety of a given rhodamine into substituted acyl benzenesulfonamides and alkylamides permits the systematic tuning of the equilibrium of spirocyclization with unprecedented accuracy and over a large range. This allows to transform the same rhodamine into either a highly fluorogenic and cell-permeable probe for live-cell stimulated emission depletion (STED) microscopy, or into a spontaneously blinking dye for single molecule localization microscopy (SMLM). We used this approach to generate differently colored probes optimized for different labeling systems and imaging applications.

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