Successful optimization of reconstruction parameters in structured illumination microscopy – A practical guide

Lachetta

et al. 2019

Preprint

Section: Coherent Illumination Of Dmdsmentioning

confidence: 99%

DMD-based super-resolution structured illumination microscopy visualizes live cell dynamics at high speed and low cost

Lachetta

et al. 2019

Preprint

“…Since it was first introduced by the laboratories of Heintzmannl 1 and Gustafsson 2 two decades ago, SIM has been evolving constantly to improve speed, resolution, and to decrease the required light dosages. Reconstruction algorithms have been developed to estimate microscope parameters robustly 3 , minimize reconstruction artifacts 4,5 , reduce the required number of raw images 6 , and check the quality of the raw data and reconstruction 7 . The primary limitation of SIM is the need to obtain a series of highquality images for each reconstructed high-resolution SIM image; this decreases temporal resolution and increases photobleaching.…”

mentioning

confidence: 99%

Deep learning enables structured illumination microscopy with low light levels and enhanced speed

et al. 2020

Structured illumination microscopy (SIM) surpasses the optical diffraction limit and offers a two-fold enhancement in resolution over diffraction limited microscopy. However, it requires both intense illumination and multiple acquisitions to produce a single high-resolution image. Using deep learning to augment SIM, we obtain a five-fold reduction in the number of raw images required for super-resolution SIM, and generate images under extreme low light conditions (at least 100× fewer photons). We validate the performance of deep neural networks on different cellular structures and achieve multi-color, live-cell super-resolution imaging with greatly reduced photobleaching.

“…The simultaneous operation of AFM with optical microscopy enables the collection of optical sectioning uorescence and nano-mechanical mapping information from a sample. However, one complication of SIM is that, in order to avoid artifacts in the nal image, requires of optimized experimental implementation, consideration of bleaching properties of the sample [30,31] and proper selection of reconstruction parameters [32,33], as SIM has a need of a complex post-processing step. Hence, coupling of AFM and SIM can also be a powerful tool to validate the results obtained with the latter.…”

Section: Image Registrationmentioning

confidence: 99%

Simultaneous 3D super-resolution fluorescence microscopy and atomic force microscopy: combined SIM and AFM platform for cell imaging

Gómez‐Varela

Stamov

Miranda

et al. 2019

Preprint

Correlating data from dierent microscopy techniques holds the potential to discover new facets of signaling events in cellular biology. Here we report for the rst time a hardware set-up capable of achieving simultaneous imaging of spatially correlated super-resolution uorescence microscopy and atomic force microscopy, a feat only obtained until now by uorescence microscopy set-ups with spatial resolution restricted to the Abbe resolution limit. We hereby remove the need to perform independent measurement and subsequent data averaging required to eliminate cell-to-cell variation in observed signals.We detail system integration, demonstrate system performance and report imaging of sub-resolution uorescent beads and genome-engineered human bone osteosarcoma epithelial cells.