Survey on CNN based super resolution methods

Super Resolution is a field of image analysis that focuses on boosting the resolution of photographs and movies without compromising detail or visual appeal, instead enhancing both. Multiple (many input images and one output image) or single (one input and one output) stages are used to convert low-resolution photos to high-resolution photos. The study examines super-resolution methods based on a convolutional neural network (CNN) for super-resolution mapping at the sub-pixel level, as well as its primary characteristics and limitations for noisy or medical images.

Survey on CNN based super resolution methods

Super Resolution is a field of image analysis that focuses on boosting the resolution of photographs and movies without compromising detail or visual appeal, instead enhancing both. Multiple (many input images and one output image) or single (one input and one output) stages are used to convert low-resolution photos to high-resolution photos. The study examines super-resolution methods based on a convolutional neural network (CNN) for super-resolution mapping at the sub-pixel level, as well as its primary characteristics and limitations for noisy or medical images.

Super-Resolution Mapping of a Chemical Reaction Driven by Plasmonic Near-Fields

Plasmonic nanoparticles have recently emerged as promising photocatalysts for light-driven chemical conversions. The illumination of these particles results in the generation of highly energetic charge carriers, elevated surface temperatures, and enhanced electromagnetic fields around them. Distinguishing between these often-overlapping processes is of paramount importance for the rational design of future plasmonic photocatalysts. However, the study of chemical reactions mediated by plasmonic effects is typically performed at the ensemble level and, therefore, limited by the intrinsic heterogeneity of the catalyst particles. Here, we report an in-situ single particle study of a chemical reaction driven solely by plasmonic near-fields. Using super-resolution fluorescence microscopy, we achieve single turnover temporal resolution and ~30 nm spatial resolution. This sub-particle accuracy permits the construction of a clear correlation between the simulated electric field distribution around individual metal nanoparticles and their super-resolved catalytic activity maps. Our results can easily be extended to systems with more complex electric field distributions, thereby guiding the design of future advanced photoactive materials.

Super-Resolution Mapping of a Chemical Reaction Driven by Plasmonic Near-Fields

Plasmonic nanoparticles have recently emerged as promising photocatalysts for light-driven chemical conversions. The illumination of these particles results in the generation of highly energetic charge carriers, elevated surface temperatures, and enhanced electromagnetic fields around them. Distinguishing between these often-overlapping processes is of paramount importance for the rational design of future plasmonic photocatalysts. However, the study of chemical reactions mediated by plasmonic effects is typically performed at the ensemble level and, therefore, limited by the intrinsic heterogeneity of the catalyst particles. Here, we report an in-situ single particle study of a chemical reaction driven solely by plasmonic near-fields. Using super-resolution fluorescence microscopy, we achieve single turnover temporal resolution and ~30 nm spatial resolution. This sub-particle accuracy permits the construction of a clear correlation between the simulated electric field distribution around individual metal nanoparticles and their super-resolved catalytic activity maps. Our results can easily be extended to systems with more complex electric field distributions, thereby guiding the design of future advanced photoactive materials.

Turn-key super-resolution mapping of cell receptor force orientation and magnitude using a commercial structured illumination microscope

Many cellular processes, including cell division, development, and cell migration require spatially and temporally coordinated forces transduced by cell surface receptors. Nucleic acid-based molecular tension probes allow one to quantify and visualize the piconewton (pN) forces applied by these receptors. Building on this technology, we recently imaged DNA tension probes using fluorescence polarization imaging to map the magnitude and 3D orientation of receptor forces with diffraction limited resolution (~ 250 nm). Further improvements in spatial resolution are desirable as many force-sensing receptors are organized at the nano-scale in supramolecular complexes such as focal adhesions. Here, we show that structured illumination microscopy (SIM), a super-resolution technique, can be used to perform super-resolution molecular force microscopy (MFM). Using SIM-MFM, we generate the highest resolution maps of both the magnitude and orientation of the pN traction forces applied by cells. We apply SIM-MFM to map platelet and fibroblast integrins forces, as well as T cell receptor forces. The method reveals that platelets dynamically re-arrange the orientation of their integrin forces during activation. Monte Carlo simulations validated the results and provided analysis of the sources of noise. Importantly, we envision that SIM-MFM will be broadly adopted by the cell biology and mechanobiology communities because it can be implemented on any standard SIM microscope without hardware modifications.