Abstract
Abstract The recent advances in super-resolution fluorescence microscopy, including single-molecule localization microscopy (SMLM), has enabled the study of previously inaccessible details, such as the organization of proteins within cellular compartments and even nanostructures in nonbiological nanomaterials, such as the polymers and semiconductors. With such developments, the need for the development of various computational nanostructure analysis methods for SMLM images is also increasing; however, this has been limited to protein cluster analysis. In this study, we developed an edge structure analysis method for pointillistic SMLM images based on the line edge roughness and power spectral density analyses. By investigating the effect of point properties in SMLM images, such as the size, density, and localization precision on the roughness measurement, we successfully demonstrated this analysis method for experimental SMLM images of actual samples, including the semiconductor line patterns, cytoskeletal elements, and cell membranes. This systematic investigation of the effect of each localization rendering parameter on edge roughness measurement provides a range for the optimal rendering parameters that preserve the relevant nanoscale structure of interest. These new methods are expected to expand our understanding of the targets by providing valuable insights into edge nanoscale structures that have not been previously obtained quantitatively.
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