Single-frame wide-field nanoscopy based on ghost imaging via sparsity constraints

The applications of present nanoscopy techniques for live cell imaging are limited by the long sampling time and low emitter density. Here we developed a new single frame wide-field nanoscopy based on ghost imaging via sparsity constraints (GISC Nanoscopy), in which a spatial random phase modulator is applied in a wide-field microscopy to achieve random measurement for fluorescence signals. This new method can effectively utilize the sparsity of fluorescence emitters to dramatically enhance the imaging resolution to 80 nm by compressive sensing (CS) reconstruction for one raw image. The ultra-high emitter density of 143 {\mu}m-2 has been achieved while the precision of single-molecule localization below 25 nm has been maintained. Thereby working with high-density of photo-switchable fluorophores GISC nanoscopy can reduce orders of magnitude sampling frames compared with previous single-molecule localization based super-resolution imaging methods.

[1]  Xiaowei Zhuang,et al.  Visualizing and discovering cellular structures with super-resolution microscopy , 2018, Science.

[2]  Wenlin Gong,et al.  A Review of Ghost Imaging via Sparsity Constraints , 2018, Applied Sciences.

[3]  Yonina C. Eldar,et al.  Sparsity-based super-resolution microscopy from correlation information. , 2018, Optics express.

[4]  Tomer Michaeli,et al.  Deep-STORM: super-resolution single-molecule microscopy by deep learning , 2018, 1801.09631.

[5]  Kam Wai Clifford Chan,et al.  High-order ghost imaging using non-Rayleigh speckle sources. , 2016, Optics express.

[6]  P. Eilers,et al.  Sparse deconvolution of high-density super-resolution images , 2016, Scientific Reports.

[7]  Stephan J Sigrist,et al.  Ultrafast, temporally stochastic STED nanoscopy of millisecond dynamics , 2015, Nature Methods.

[8]  Zhishen Tong,et al.  Spectral Camera based on Ghost Imaging via Sparsity Constraints , 2015, Scientific Reports.

[9]  Yonina C. Eldar,et al.  Single-shot sparsity-based sub-wavelength fluorescence imaging of biological structures using dictionary learning , 2015, 2015 Conference on Lasers and Electro-Optics (CLEO).

[10]  Jian Wang.  Support Recovery With Orthogonal Matching Pursuit in the Presence of Noise , 2015, IEEE Transactions on Signal Processing.

[11]  Guy M. Hagen,et al.  ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging , 2014, Bioinform..

[12]  Ling-An Wu,et al.  Lensless ghost imaging with sunlight. , 2014, Optics letters.

[13]  Michael W. Davidson,et al.  Video-rate nanoscopy enabled by sCMOS camera-specific single-molecule localization algorithms , 2013, Nature Methods.

[14]  M. Schnitzer,et al.  Unified resolution bounds for conventional and stochastic localization fluorescence microscopy. , 2012, Physical review letters.

[15]  Shensheng Han,et al.  Quantum limits of super-resolution of optical sparse objects via sparsity constraint. , 2012, Optics express.

[16]  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.

[17]  R. Boyd,et al.  The physics of ghost imaging , 2012, Quantum Inf. Process..

[18]  Y. Shih.  The physics of ghost imaging: nonlocal interference or local intensity fluctuation correlation? , 2012, Quantum Inf. Process..

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

[20]  Emmanuel J. Candès,et al.  Towards a Mathematical Theory of Super‐resolution , 2012, ArXiv.

[21]  Wenlin Gong,et al.  Experimental investigation of the quality of lensless super-resolution ghost imaging via sparsity constraints , 2012 .

[22]  Wenlin Gong,et al.  Ghost imaging lidar via sparsity constraints , 2012, 1203.3835.

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

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

[25]  Wenlin Gong,et al.  The effect of spatial transverse coherence property of a thermal source on Ghost imaging and Ghost imaging via compressive sampling , 2009, 0912.4808.

[26]  Wenlin Gong,et al.  Super-resolution ghost imaging via compressive sampling reconstruction , 2009, 0910.4823.

[27]  Bryant B. Chhun,et al.  Super-Resolution Video Microscopy of Live Cells by Structured Illumination , 2009, Nature Methods.

[28]  Wenlin Gong,et al.  Improving resolution by the second-order correlation of light fields. , 2009, Optics letters.

[29]  E.J. Candes,et al.  An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[30]  Mário A. T. Figueiredo,et al.  Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems , 2007, IEEE Journal of Selected Topics in Signal Processing.

[31]  Joel A. Tropp,et al.  Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit , 2007, IEEE Transactions on Information Theory.

[32]  R. Hochstrasser,et al.  Wide-field subdiffraction imaging by accumulated binding of diffusing probes , 2006, Proceedings of the National Academy of Sciences.

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

[34]  E. Candès,et al.  Sparsity and incoherence in compressive sampling , 2006, math/0611957.

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

[36]  Christian Eggeling,et al.  Breaking the diffraction barrier in fluorescence microscopy at low light intensities by using reversibly photoswitchable proteins. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[37]  M. Gustafsson.  Nonlinear structured-illumination microscopy: wide-field fluorescence imaging with theoretically unlimited resolution. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[38]  Ling-An Wu,et al.  Correlated two-photon imaging with true thermal light. , 2005, Optics letters.

[39]  Shensheng Han,et al.  Incoherent coincidence imaging and its applicability in X-ray diffraction. , 2004, Physical review letters.

[40]  Moon Gi Kang,et al.  Super-resolution image reconstruction: a technical overview , 2003, IEEE Signal Process. Mag..

[41]  S. Hell,et al.  Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy. , 1994, Optics letters.

[42]  Y. Shih,et al.  Quantum Imaging , 2007, IEEE Journal of Selected Topics in Quantum Electronics.

[43]  O REN S OLOMON,et al.  Sparsity-based super-resolution microscopy from correlation information , 2018 .

[44]  Mikhail I. Kolobov,et al.  Quantum imaging , 2009, 2009 Conference on Lasers & Electro Optics & The Pacific Rim Conference on Lasers and Electro-Optics.