FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

Super resolution microscopy such as STORM and (F)PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow temporal resolution which is a serious limitation when investigating live-cell dynamics. Here, we present an algorithm for high-density super-resolution microscopy which combines a sparsity-promoting formulation with a Taylor series approximation of the PSF. Our algorithm is designed to provide unbiased localization on continuous space and high recall rates for high-density imaging, and to have orders-of-magnitude shorter run times compared to previous high-density algorithms. We validated our algorithm on both simulated and experimental data, and demonstrated live-cell imaging with temporal resolution of 2.5 seconds by recovering fast ER dynamics.

[1]  M. Andreeff,et al.  Cell Proliferation and Differentiation , 2003 .

[2]  J. Lippincott-Schwartz,et al.  Imaging Intracellular Fluorescent Proteins at Nanometer Resolution , 2006, Science.

[3]  Michael D. Mason,et al.  Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. , 2006, Biophysical journal.

[4]  Michael J Rust,et al.  Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM) , 2006, Nature Methods.

[5]  E. Betzig,et al.  Live-cell photoactivated localization microscopy of nanoscale adhesion dynamics , 2008, Nature Methods.

[6]  S. Weiss,et al.  Fast, background-free, 3D super-resolution optical fluctuation imaging (SOFI) , 2009, Proceedings of the National Academy of Sciences.

[7]  C. M. Galloway,et al.  An Iterative Algorithm for Background Removal in Spectroscopy by Wavelet Transforms , 2009, Applied spectroscopy.

[8]  José M. Bioucas-Dias,et al.  Fast Image Recovery Using Variable Splitting and Constrained Optimization , 2009, IEEE Transactions on Image Processing.

[9]  Keith A. Lidke,et al.  Fast, single-molecule localization that achieves theoretically minimum uncertainty , 2010, Nature Methods.

[10]  C. Zimmer,et al.  QuickPALM: 3D real-time photoactivation nanoscopy image processing in ImageJ , 2010, Nature Methods.

[11]  Michael J Rust,et al.  Sub-Diffraction-Limit Imaging with Stochastic Optical Reconstruction Microscopy , 2010 .

[12]  Junjie Hu,et al.  Weaving the Web of ER Tubules , 2011, Cell.

[13]  S. Holden,et al.  DAOSTORM: an algorithm for high- density super-resolution microscopy , 2011, Nature Methods.

[14]  Chenglong Xia,et al.  Super-resolution fluorescence imaging of organelles in live cells with photoswitchable membrane probes , 2012, Proceedings of the National Academy of Sciences.

[15]  Dylan T Burnette,et al.  Bayesian localisation microscopy reveals nanoscale podosome dynamics , 2011, Nature Methods.

[16]  Nicholas A. Frost,et al.  Optimization of Cell Morphology Measurement via Single-Molecule Tracking PALM , 2012, PloS one.

[17]  X. Zhuang,et al.  Statistical deconvolution for superresolution fluorescence microscopy. , 2012, Biophysical journal.

[18]  R. Parthasarathy.  Rapid, accurate particle tracking by calculation of radial symmetry centers , 2012, Nature Methods.

[19]  Lei Zhu,et al.  Faster STORM using compressed sensing , 2012, Nature Methods.

[20]  Sjoerd Stallinga,et al.  Measuring image resolution in optical nanoscopy , 2013, Nature Methods.

[21]  Boyd Fowler.  Highlights of the International Image Sensor Workshop , 2013 .

[22]  Xiaowei Zhuang,et al.  Fast compressed sensing analysis for super-resolution imaging using L1-homotopy. , 2013, Optics express.

[23]  B. Fowler,et al.  Read Noise Distribution Modeling for CMOS Image Sensors , 2013 .

[24]  Suliana Manley,et al.  Simple buffers for 3D STORM microscopy , 2013, Biomedical optics express.

[25]  Andrew G. York,et al.  Instant super-resolution imaging in live cells and embryos via analog image processing , 2013, Nature Methods.

[26]  Ying Hu,et al.  Accelerating 3B single-molecule super-resolution microscopy with cloud computing , 2013, Nature Methods.

[27]  J. C. Ye,et al.  Fast Maximum Likelihood High-Density Low-SNR Super-Resolution Localization Microscopy , 2013 .

[28]  Hope T. Beier,et al.  Experimental Comparison of the High-Speed Imaging Performance of an EM-CCD and sCMOS Camera in a Dynamic Live-Cell Imaging Test Case , 2014, PloS one.