4.7 Article

Enhanced super-resolution microscopy by extreme value based emitter recovery

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Multidisciplinary Sciences

Accurate and rapid background estimation in single-molecule localization microscopy using the deep neural network BGnet

Leonhard Mockl et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2020)

Article Multidisciplinary Sciences

A simple and cost-effective setup for super-resolution localization microscopy

Hongqiang Ma et al.

SCIENTIFIC REPORTS (2017)

Article Multidisciplinary Sciences

Fast and Precise 3D Fluorophore Localization based on Gradient Fitting

Hongqiang Ma et al.

SCIENTIFIC REPORTS (2015)

Editorial Material Biochemical Research Methods

Taming the image background beast

Daniel Evanko

NATURE METHODS (2014)

Review Biochemical Research Methods

Fluorophore localization algorithms for super-resolution microscopy

Alex Small et al.

NATURE METHODS (2014)

Review Biochemical Research Methods

Precisely and accurately localizing single emitters in fluorescence microscopy

Hendrik Deschout et al.

NATURE METHODS (2014)

Article Biochemical Research Methods

Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms

Fang Huang et al.

NATURE METHODS (2013)

Article Optics

Localization-based super-resolution microscopy with an sCMOS camera

Zhen-Li Huang et al.

OPTICS EXPRESS (2011)

Article Chemistry, Multidisciplinary

Subdiffraction-resolution fluorescence imaging with conventional fluorescent probes

Mike Heilemann et al.

ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2008)

Article Biochemical Research Methods

Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM)

Michael J. Rust et al.

NATURE METHODS (2006)

Article Multidisciplinary Sciences

Imaging intracellular fluorescent proteins at nanometer resolution

Eric Betzig et al.

SCIENCE (2006)

Article Computer Science, Artificial Intelligence

Image quality assessment: From error visibility to structural similarity

Z Wang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2004)