SOLAR-STORM: Fast and Robust 3D Localization of Fluorophores in Dense Clusters

Stochastic switching-based super-resolution microscopy provides an order of magnitude resolution improvement to conventional diffraction-limited microscopy by separating fluorophores in the time domain and localizing them with high precision. This trade-off between spatial and temporal resolution can be mitigated by increasing the density of fluorophores in each frame. However, conventional algorithms can only detect well-separated single emitter events, rejecting many fluorophores in dense clusters.
Here, we introduce a fast and precise algorithm that localizes fluorophores in dense clusters in 3D, namely Spline-fitting and Orthogonal matching pursuit (OMP) based Localization Algorithm for Reconstructing STORM images (SOLAR-STORM). SOLAR-STORM provides the 3D coordinates of fluorophores in dense scenes on a continuous space by Taylor-expanding the spline-fitted point spread function (PSF). It contains an inherent parallel structure that allows significant acceleration when implemented on GPUs. This approach provides fast and robust 3D reconstruction with any given PSF, suggesting that this method can be widely used for different fluorescence microscopy techniques for imaging biological systems.