Optical Super-resolution Imaging under Different Fluorescence Temporal Fluctuations

Fluorescence fluctuation-based super-resolution microscopy is a cost-effective and widely applicable super-resolution microscopic technology, which has broad applications in observing subcellular structures and monitoring their kinetic processes. However, it is highly demanded to systematically study the reconstruction quality of various fluctuation-based superresolution algorithms under different fluorescence temporal fluctuations. In this paper, firstly, the performances in the image quality of multiple algorithms under different conditions are quantitatively analyzed and compared by employing various evaluation metrics such as Resolution Scaled Pearson’s coefficient (RSP), Resolution Scaled Error (RSE), Signal-to-Noise Ratios (SNRs), Relative error of strength (K), and Resolution (R). Then, a comprehensive evaluation factor (CEF) was defined by combining 5 parameters for the evaluation of all algorithms, and the advantages and applicable conditions of various algorithms are summarized and analyzed. Furthermore, this paper establishes a general model using a multi-layer perceptron (MLP) to accurately predict the most suitable super-resolution algorithms under different conditions. In addition, a software platform for multi-algorithm fluorescence fluctuation super-resolution nanoscopy was developed, which can realize the generation of fluorescence fluctuation signals, synchronize multiple super-resolution algorithms, and the evaluation of reconstructed images. The results show that high-quality super-resolution images can be obtained by increasing image frames together with enhancing the fluorescence fluctuation signals. The model of the multilayer perceptron performs well with high output accuracy (>95%) after multiple iterations of training and exhibits good prediction capability that can reduce additional experiments and improve experimental efficiency. These studies will facilitate the implementation of fluctuation-based super-resolution techniques for the research of subcellular organelle investigation under various fluorescent labeling conditions.