基于压缩感知的高密度分子定位算法比较
[1] Hell S W, Wichmann J. Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy[J]. Optics Letters, 1994, 19(11): 780-782.
[2] Gustafsson M G. Nonlinear structured-illumination microscopy: wide-field fluorescence imaging with theoretically unlimited resolution[J]. Proceedings of National Academy Sciences of the United States of America, 2005, 102(37): 13081-13086.
[3] Rust M J, Bates M, Zhuang X. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM) [J]. Nature Methods, 2006, 3(10): 793-796.
[4] Hess S T, Girirajan T P K, Mason M D. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy[J]. Biophysical Journal, 2006, 91(11): 4258-4272.
[5] Thompson R E, Larson D R , Webb W W. Precise nanometer localization analysis for individual fluorescent probes[J]. Biophysical Journal, 2002, 82(5): 2775-2783.
[6] Aguet F, van de Ville D, Unser M. A maximum-likelihood formalism for sub-resolution axial localization of fluorescent nanoparticles[J]. Optics Express, 2005, 13(26): 10503-10522.
[7] 于斌, 陈丹妮, 刘磊, 等. 荧光单分子的频率域纳米级快速定位算法及其在超分辨荧光成像中的应用[J]. 光学学报, 2012, 32(2): 0218001.
[8] Yu B, Chen D N, Qu J L, et al. Fast Fourier domain localization algorithm of a single molecule with nanometer precision[J]. Optics Letters, 2011, 36(22): 4317-4319.
[9] Holden S J, Uphoff S,Kapanidis A N. DAOSTORM: an algorithm for high-density super-resolution microscopy[J]. Nature Methods, 2011, 8(4): 279-280.
[10] Quan T W, Zhu H Y, Liu X M, et al. High-density localization of active molecules using structured sparse model and bayesian information criterion[J]. Optics Express, 2011, 19(18): 16963-16974.
[11] Zhu L, Zhang W, Elnatan D, et al. Faster STORM using compressed sensing[J]. Nature Methods, 2012, 9(7): 721-723.
[12] Babcock H P, Moffitt J R, Cao Y L, et al. Fast compressed sensing analysis for super-resolution imaging using L1-homotopy[J]. Optics Express, 2013, 21(23): 28583-28596.
[13] Cheng T, Chen D N, Yu B, et al. Reconstruction of super-resolution STORM images using compressed sensing based on low-resolution raw images and interpolation[J]. Biomedical Optics Express, 2017, 8(5): 2445-2457.
[14] Zhang S W, Chen D N, Niu H B. 3D localization of high particle density images using sparse recovery[J]. Applied Optics, 2015, 54(26): 7859-7864.
[15] Du Y J, Zhang H,Zhao M Y, et al. Faster super-resolution imaging of high density molecules via a cascading algorithm based on compressed sensing[J]. Optics Express, 2015, 23(14): 18563-18576.
[16] Gu L S, Sheng Y, Chen Y, et al. High-density 3D single molecular analysis based on compressed sensing[J]. Biophysical Journal, 2014, 106(11): 2443-2449.
[17] Huang J Q, Gumpper K, Chi Y J, et al. Fast two-dimensional super-resolution image reconstruction algorithm for ultra-high emitter density[J]. Optics Letters, 2015, 40(13): 2989-2992.
[18] Daubechies I, Fornasier M, Loris I. Accelerated projected gradient method for linear inverse problems with sparsity constraints[J]. Journal of Fourier Analysis and Applications, 2008, 14(5/6): 764-792.
[19] Figueiredo M A, Nowak R D, Wright S J. Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems[J]. IEEE Journal of Selected Topics in Signal Processing, 2007, 1(4): 586-597.
[20] Parikh N, Boyd S. Proximal algorithms[M]. Boston: Now Publishers, 2014, 1(3): 127-239.
[21] Boyd S, Parikh N, Chu E, et al. Distributed Optimization and Statistical Learning via the alternating direction method of multipliers[J]. Foundations and Trends in Machine Learning, 2010, 3(1): 1-122.
[22] Beck A, Teboulle M. A fast iterative shrinkage-thresholding algorithm for linear inverse problems[J]. SIAM Journal on Imaging Sciences, 2009, 2(1): 183-202.
[23] Donoho D L, Tsaig Y. Fast solution of L1-norm minimization problems when the solution may be sparse[J]. IEEE Transactions on Information Theory, 2008, 54(11): 4789-4812.
[24] Cai T T, Wang L. Orthogonal matching pursuit for sparse signal recovery with noise[J]. IEEE Transactions on Information Theory, 2011, 57(7): 4680-4688.
[25] Hugelier S, de Rooi J J, Bernex R, et al. Sparse deconvolution of high-density super-resolution images[J]. Scientific Reports, 2016, 6: 21413.
[26] http://bigwww.epfl.ch/smlm/.
张赛文, 于斌, 陈丹妮, 吴晶晶, 李四维, 屈军乐. 基于压缩感知的高密度分子定位算法比较[J]. 中国激光, 2018, 45(3): 0307014. Zhang Saiwen, Yu Bin, Chen Danni, Wu Jingjing, Li Siwei, Qu Junle. Comparison of Algorithms of High-Density Molecule Localization Based on Compressed Sensing[J]. Chinese Journal of Lasers, 2018, 45(3): 0307014.