Embracing the uncertainty: the evolution of SOFI into a diverse family of fluctuation-based super-resolution microscopy methods

Abstract Super-resolution microscopy techniques have pushed-down the limits of resolution in optical imaging by more than an order magnitude. However, these methods often require long acquisition times addition to complex setups and sample preparation protocols. fluctuation (SOFI) emerged over ten years ago as approach that exploits temporal spatial correlations within acquired images obtain increased with less strict requirements. This review follows progress SOFI from its first demonstration development a branch treat fluctuations source contrast, rather noise. Among others, we highlight implementation standard fluorescent proteins well microscope modifications facilitate 3D application modern cameras. Going beyond classical framework SOFI, explore different innovative concepts deep neural networks all way quantum analogue antibunching microscopy. While has not reached same level ubiquity other super-resolution methods, our overview finds significant substantial potential for concept leveraging fluorescence super-resolved images.