3.2.2 eSRRF
NanoPyx's enhanced Super-Resolution Radial Fluctuations (eSRRF) method builds on the original SRRF technique to generate even higher quality super-resolved images. eSRRF enhances the SRRF algorithm by incorporating additional computational refinements and optimizations, which improve the precision and accuracy of emitter localization. This method processes temporal fluctuations in standard fluorescence microscopy image sequences, analyzing radial symmetry and intensity variations to achieve sub-diffraction limit resolution. eSRRF produces sharper images with better contrast and resolution, allowing for detailed visualization of cellular structures and dynamics. The improvements in eSRRF make it particularly effective for live-cell imaging, as it provides super-resolved images with minimal phototoxicity and photobleaching, thus enabling extended observation of biological processes with exceptional clarity.
Reference: Laine RF, Heil HS, Coelho S et al 2023 Nat Methods.
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Image Stack: The image stack to be processed, required to with shape: (time, rows, columns).
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Magnification: Desired magnification for the generated radiality image.
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Sensitivity: Exponential factor of RGC calculation, defaults to 1. Higher values will lead to more sharpening.
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Ring Radius: Radius of the ring used to calculate the radiality (in pixels).
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Frames Per Time Point: How many frames are used to calculated individual timepoints. For example, given an input image with 500 frames, if using 100 frames per timepoint, SRRF will generate an image stack with 5 super-resolved frames. Defaults to using every frame to calculate a single timepoint.
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Apply Intensity Weighting: Whether to calculate intensity values based on the original image fluorescence intensity as opposed to just outputting the radiality values.
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Reconstruction: Type of temporal reconstruction.