Super-resolution Microscope Based on Laser Scanning and a Microsphere Lens

Author(s):  
Kuan-Yu Li ◽  
Yun-Ju Liu ◽  
Yang Tsao ◽  
Kung-Hsuan Lin ◽  
Chih-Wei Chang ◽  
...  
2021 ◽  
Author(s):  
Kentaro Nishida ◽  
Hikaru Sato ◽  
Ryosuke Oketani ◽  
Kentaro Mochizuki ◽  
Kenta Temma ◽  
...  

Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 861
Author(s):  
Jacopo Cardellini ◽  
Arianna Balestri ◽  
Costanza Montis ◽  
Debora Berti

In the past decade(s), fluorescence microscopy and laser scanning confocal microscopy (LSCM) have been widely employed to investigate biological and biomimetic systems for pharmaceutical applications, to determine the localization of drugs in tissues or entire organisms or the extent of their cellular uptake (in vitro). However, the diffraction limit of light, which limits the resolution to hundreds of nanometers, has for long time restricted the extent and quality of information and insight achievable through these techniques. The advent of super-resolution microscopic techniques, recognized with the 2014 Nobel prize in Chemistry, revolutionized the field thanks to the possibility to achieve nanometric resolution, i.e., the typical scale length of chemical and biological phenomena. Since then, fluorescence microscopy-related techniques have acquired renewed interest for the scientific community, both from the perspective of instrument/techniques development and from the perspective of the advanced scientific applications. In this contribution we will review the application of these techniques to the field of drug delivery, discussing how the latest advancements of static and dynamic methodologies have tremendously expanded the experimental opportunities for the characterization of drug delivery systems and for the understanding of their behaviour in biologically relevant environments.


2021 ◽  
Author(s):  
Esley Torres ◽  
Raúl Pinto ◽  
Alejandro Linares ◽  
Damián Martínez ◽  
Víctor Abonza ◽  
...  

Mean-Shift Super Resolution (MSSR) is a principle based on the Mean Shift theory that improves the spatial resolution in fluorescence images beyond the diffraction limit. MSSR works on low- and high-density fluorophore images, is not limited by the architecture of the detector (EM-CCD, sCMOS, or photomultiplier-based laser scanning systems) and is applicable to single images as well as temporal series. The theoretical limit of spatial resolution, based on optimized real-world imaging conditions and analysis of temporal image series, has been measured to be 40 nm. Furthermore, MSSR has denoising capabilities that outperform other analytical super resolution image approaches. Altogether, MSSR is a powerful, flexible, and generic tool for multidimensional and live cell imaging applications.


2021 ◽  
Author(s):  
Esley García ◽  
Raúl Cámara ◽  
Alejandro Linares ◽  
Damián Martínez ◽  
Víctor Abonza ◽  
...  

Abstract Mean-Shift Super Resolution (MSSR) is a principle based on the Mean Shift theory that improves the spatial resolution in fluorescence images beyond the diffraction limit. MSSR works on low- and high-density fluorophore images, is not limited by the architecture of the detector (EM-CCD, sCMOS, or photomultiplier-based laser scanning systems) and is applicable to single images as well as temporal series. The theoretical limit of spatial resolution, based on optimized real-world imaging conditions and analysis of temporal image series, has been measured to be 40 nm. Furthermore, MSSR has denoising capabilities that outperform other analytical super resolution image approaches. Altogether, MSSR is a powerful, flexible, and generic tool for multidimensional and live cell imaging applications.


2021 ◽  
pp. 1-28
Author(s):  
Giorgio Tortarolo ◽  
Marco Castello ◽  
Giuseppe Vicidomini

Nano Letters ◽  
2009 ◽  
Vol 9 (11) ◽  
pp. 3883-3889 ◽  
Author(s):  
Ju Lu ◽  
Wei Min ◽  
José-Angel Conchello ◽  
Xiaoliang Sunney Xie ◽  
Jeff W. Lichtman

Author(s):  
Christian Pilger ◽  
Jakub Pospíšil ◽  
Marcel Müller ◽  
Martin Ruoff ◽  
Martin Schütte ◽  
...  

Fluorescence-based microscopy as one of the standard tools in biomedical research benefits more and more from super-resolution methods, which offer enhanced spatial resolution allowing insights into new biological processes. A typical drawback of using these methods is the need for new, complex optical set-ups. This becomes even more significant when using two-photon fluorescence excitation, which offers deep tissue imaging and excellent z-sectioning. We show that the generation of striped-illumination patterns in two-photon laser scanning microscopy can readily be exploited for achieving optical super-resolution and contrast enhancement using open-source image reconstruction software. The special appeal of this approach is that even in the case of a commercial two-photon laser scanning microscope no optomechanical modifications are required to achieve this modality. Modifying the scanning software with a custom-written macro to address the scanning mirrors in combination with rapid intensity switching by an electro-optic modulator is sufficient to accomplish the acquisition of two-photon striped-illumination patterns on an sCMOS camera. We demonstrate and analyse the resulting resolution improvement by applying different recently published image resolution evaluation procedures to the reconstructed filtered widefield and super-resolved images. This article is part of the Theo Murphy meeting issue ‘Super-resolution structured illumination microscopy (part 1)'.


2020 ◽  
Vol 238 ◽  
pp. 06014
Author(s):  
Stefan Siemens ◽  
Markus Kästner ◽  
Eduard Reithmeier

In this work super-resolution imaging is used to enhance 2.5D height data of thermal sprayed Al2O3 ceramics with stochastically microstructured surfaces. The data is obtained by means of a confocal laser scanning microscope. By implementing and training a Very Deep Super-Resolution neural network to generate residual images an improvement of the peak signal-to-noise ratio and structural similarity index can be observed when compared to classic interpolation methods.


2015 ◽  
Author(s):  
Kuan-Yu Li ◽  
Yun-Ju Liu ◽  
Zong-Xing Lou ◽  
Yang Tsao ◽  
Kung-Hsuan Lin ◽  
...  

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