Abstract

Compressive fluorescence microscopy has been proposed as a promising approach for fast acquisitions at sub-Nyquist sampling rates. Given that signal-to-noise ratio (SNR) is very important in the design of fluorescence microscopy systems, a new saliency-guided sparse reconstruction ensemble fusion system has been proposed for improving SNR in compressive fluorescence microscopy. This system produces an ensemble of sparse reconstructions using adaptively optimized probability density functions derived based on underlying saliency rather than the common uniform random sampling approach. The ensemble of sparse reconstructions are then fused together via ensemble expectation merging. Experimental results using real fluorescence microscopy data sets show that significantly improved SNR can be achieved when compared to existing compressive fluorescence microscopy approaches, with SNR increases of 16-9 dB within the noise range of 1.5%–10% standard deviation at the same compression rate.

© 2012 OSA

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2010 (2)

M. Marim and E. Angelini, “Denoising in fluorescence microscopy using compressed sensing with multiple reconstructions and non-local merging,” Eng. Med. Biol. (EMBC), 2010 Annual International Conference of the IEEE3394(7), 3394–3397 (2010).
[CrossRef]

Y. Wu, P. Ye, I. O. Mirza, G. R. Arce, and D. W. Prather, “Experimental demonstration of an optical-sectioning compressive sensing microscope (csm),” Opt. Express18, 24565–24578 (2010).
[CrossRef] [PubMed]

2009 (3)

A. Beck and M. Teboulle, “Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems,” IEEE Trans. Imag. Proc.18(11), 2419–2434 (2009).
[CrossRef]

A. Beck and M. Teboulle, “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,” SIAM J. Imag. Sci.1, 183–202 (2009).
[CrossRef]

M. Marim, E. Angelini, and J. C. Olivo-Marin, “Compressed sensing in biological microscopy,” in Proc. SPIE Wavelets XIII7446, 3394–3397 (2009).

2008 (3)

R. Baraniuk, M. Davenport, R. DeVore, and M. Wakin, “A simple proof of the restricted isometry property for random matrices,” Const. App.28(3), 253–263 (2008).
[CrossRef]

J. B. Pawley and B. R. Masters, “Handbook of biological confocal microscopy, third edition,” J. Bio-Med. Opt.13(029902), (2008).

E. J. Candes, “Restricted isometry property and its implications for compressed sensing,” Comptes rendus - Mathematique346(9–10), 589–592 (2008).

2007 (1)

H. R. Petty, “Fluorescence microscopy: Established and emerging methods, experimental strategies, and applications in immunology,” Microsc. Res. Tech.70(8), 687–709 (2007).
[CrossRef] [PubMed]

2006 (4)

E. Candes and J. Romberg, “Quantitative robust uncertainty principles and optimally sparse decompositions,” Found. Comput. Math.6(2), 227–254 (2006).
[CrossRef]

E. Candes, J. Romberg, and T. Tao, “Stable signal recovery from incomplete and inaccurate measurements,” Commun. Pure Appl. Math.59(8), 1207–1221 (2006).
[CrossRef]

D. Donoho, “Compressed sensing,” IEEE Trans. Inform. Theory.52(4), 1289–1306 (2006).
[CrossRef]

J. Romberg, E. Candes, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inform. Theory.52(2), 489–509 (2006).
[CrossRef]

2005 (1)

W. C. Moss, S. Haase, J. M. Lyle, D. A. Agard, and J. W. Sedat, “A novel 3d wavelet-based filter for visualizing features in noisy biological data,” J. Microscopy219, 43–49 (2005).
[CrossRef]

2004 (2)

B. R. Renikuntla, H. C. Rose, J. Eldol, A. S. Waggoner, and B. A. Armitage, “Improved photostability and fluorescence properties through polyfluorination of a cyanine dye,” Organic. Lett.6(6), 909–912 (2004).
[CrossRef]

R. Connally, D. Veal, and J. Piper, “Flash lamp-excited time-resolved fluorescence microscope suppresses autofluorescence in water concentrates to deliver an 11-fold increase in signal-to-noise ratio,” J. Biomed. Opt.9, 725–734 (2004).
[CrossRef] [PubMed]

2003 (2)

R. Connally, D. Veal, and J. Piper, “Novel flashlamp based timeresolved fluorescence microscope reduces autofluorescence for 30-fold contrast enhancement in environmental samples,” Proc. SPIE4964, 14–23 (2003).
[CrossRef]

J. Zakrzewski, “Integrating a spectrometer with an optical microscope presents challenges,” SPIE Magazine pp. 29 (2003).

2002 (1)

R. Connally, D. Veal, and J. Piper, “High resolution detection of fluorescently labeled microorganisms in environmental samples using time-resolved fluorescence microscopy,” FEMS Microbiol Ecol41, 239–245 (2002).
[CrossRef] [PubMed]

1999 (1)

N. Panchuk-Voloshina, R. P. Haugland, J. Bishop-Stewart, M. K. Bhalgat, P. J. Millard, F. Mao, W. Leung, and R. P. Haugland, “Alexa dyes, a series of new fluorescent dyes that yield exceptionally bright, photostable conjugates,” J. Histochem. Cytochem.47, 1179–1188 (1999).
[CrossRef] [PubMed]

1998 (1)

D. Piston, “Choosing objective lenses: The importance of numerical aperture and magnification in digital microscopy,” The Biological Bulletin195, 1–4 (1998).
[CrossRef] [PubMed]

1997 (1)

S. Sabri, F. Richelme, A. Pierres, A. Benoliel, and P. Bongrand, “Interest of image processing in cell biology and immunology,” J. Immunol. Methods.208, 1–27 (1997).
[CrossRef]

1995 (1)

L. Song, E. J. Hennink, T. Young, and H. J. Tanke, “Photobleaching kinetics of fluorescein in quantitative fluorescence microscopy,” Biophys. J.68, 2588–2600 (1995).
[CrossRef] [PubMed]

1990 (2)

R. A. Mathies, K. Peck, and L. Stryer, “Optimization of high-sensitivity fluorescence detection,” Anal. Chem.62, 1786–1791 (1990).
[CrossRef] [PubMed]

P. Perona and J. Malik, “Scale-space and edge detection using anisotropic diffusion,” IEEE Trans. Pattern. Anal. Mach. Intell.12, 629–639 (1990).
[CrossRef]

Achanta, R.

R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk, “Frequency-tuned salient region detection,” IEEE International Conference on Computer Vision and Pattern Recognitio pp. 1597–1604 (2009).
[CrossRef]

Agard, D. A.

W. C. Moss, S. Haase, J. M. Lyle, D. A. Agard, and J. W. Sedat, “A novel 3d wavelet-based filter for visualizing features in noisy biological data,” J. Microscopy219, 43–49 (2005).
[CrossRef]

Angelini, E.

M. Marim and E. Angelini, “Denoising in fluorescence microscopy using compressed sensing with multiple reconstructions and non-local merging,” Eng. Med. Biol. (EMBC), 2010 Annual International Conference of the IEEE3394(7), 3394–3397 (2010).
[CrossRef]

M. Marim, E. Angelini, and J. C. Olivo-Marin, “Compressed sensing in biological microscopy,” in Proc. SPIE Wavelets XIII7446, 3394–3397 (2009).

Arce, G. R.

Armitage, B. A.

B. R. Renikuntla, H. C. Rose, J. Eldol, A. S. Waggoner, and B. A. Armitage, “Improved photostability and fluorescence properties through polyfluorination of a cyanine dye,” Organic. Lett.6(6), 909–912 (2004).
[CrossRef]

Baraniuk, R.

R. Baraniuk, M. Davenport, R. DeVore, and M. Wakin, “A simple proof of the restricted isometry property for random matrices,” Const. App.28(3), 253–263 (2008).
[CrossRef]

Beck, A.

A. Beck and M. Teboulle, “Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems,” IEEE Trans. Imag. Proc.18(11), 2419–2434 (2009).
[CrossRef]

A. Beck and M. Teboulle, “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,” SIAM J. Imag. Sci.1, 183–202 (2009).
[CrossRef]

Benoliel, A.

S. Sabri, F. Richelme, A. Pierres, A. Benoliel, and P. Bongrand, “Interest of image processing in cell biology and immunology,” J. Immunol. Methods.208, 1–27 (1997).
[CrossRef]

Bhalgat, M. K.

N. Panchuk-Voloshina, R. P. Haugland, J. Bishop-Stewart, M. K. Bhalgat, P. J. Millard, F. Mao, W. Leung, and R. P. Haugland, “Alexa dyes, a series of new fluorescent dyes that yield exceptionally bright, photostable conjugates,” J. Histochem. Cytochem.47, 1179–1188 (1999).
[CrossRef] [PubMed]

Bishop-Stewart, J.

N. Panchuk-Voloshina, R. P. Haugland, J. Bishop-Stewart, M. K. Bhalgat, P. J. Millard, F. Mao, W. Leung, and R. P. Haugland, “Alexa dyes, a series of new fluorescent dyes that yield exceptionally bright, photostable conjugates,” J. Histochem. Cytochem.47, 1179–1188 (1999).
[CrossRef] [PubMed]

Bobin, J.

V. Studer, J. Bobin, M. Chahid, H. Moussavi, E. J. Candes, and M. Dahan, “Compressive fluorescence microscopy for biological and hyperspectral imaging,” Proceedings of the National Academy of Sciences of the United States of America pp. 10 (2011).

Bongrand, P.

S. Sabri, F. Richelme, A. Pierres, A. Benoliel, and P. Bongrand, “Interest of image processing in cell biology and immunology,” J. Immunol. Methods.208, 1–27 (1997).
[CrossRef]

Candes, E.

E. Candes and J. Romberg, “Quantitative robust uncertainty principles and optimally sparse decompositions,” Found. Comput. Math.6(2), 227–254 (2006).
[CrossRef]

E. Candes, J. Romberg, and T. Tao, “Stable signal recovery from incomplete and inaccurate measurements,” Commun. Pure Appl. Math.59(8), 1207–1221 (2006).
[CrossRef]

J. Romberg, E. Candes, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inform. Theory.52(2), 489–509 (2006).
[CrossRef]

Candes, E. J.

E. J. Candes, “Restricted isometry property and its implications for compressed sensing,” Comptes rendus - Mathematique346(9–10), 589–592 (2008).

V. Studer, J. Bobin, M. Chahid, H. Moussavi, E. J. Candes, and M. Dahan, “Compressive fluorescence microscopy for biological and hyperspectral imaging,” Proceedings of the National Academy of Sciences of the United States of America pp. 10 (2011).

Chahid, M.

V. Studer, J. Bobin, M. Chahid, H. Moussavi, E. J. Candes, and M. Dahan, “Compressive fluorescence microscopy for biological and hyperspectral imaging,” Proceedings of the National Academy of Sciences of the United States of America pp. 10 (2011).

Clausi, D. A.

S. Schwartz, A. Wong, and D. A. Clausi, “Saliency-guided compressive fluorescence microscopy” In 34th Int. Conf. Eng. Med. Biol. (EMBC 2012) (to be published).

S. Schwartz, A. Wong, and D. A. Clausi, “Saliency-guided compressive sensing approach to efficient laser range measurement,” J. Visual Commun. Image Represent. (DOI: http://dx..org/10.1016/j.jvcir.2012.02.002 ), (2012).
[CrossRef]

Connally, R.

R. Connally, D. Veal, and J. Piper, “Flash lamp-excited time-resolved fluorescence microscope suppresses autofluorescence in water concentrates to deliver an 11-fold increase in signal-to-noise ratio,” J. Biomed. Opt.9, 725–734 (2004).
[CrossRef] [PubMed]

R. Connally, D. Veal, and J. Piper, “Novel flashlamp based timeresolved fluorescence microscope reduces autofluorescence for 30-fold contrast enhancement in environmental samples,” Proc. SPIE4964, 14–23 (2003).
[CrossRef]

R. Connally, D. Veal, and J. Piper, “High resolution detection of fluorescently labeled microorganisms in environmental samples using time-resolved fluorescence microscopy,” FEMS Microbiol Ecol41, 239–245 (2002).
[CrossRef] [PubMed]

Dahan, M.

V. Studer, J. Bobin, M. Chahid, H. Moussavi, E. J. Candes, and M. Dahan, “Compressive fluorescence microscopy for biological and hyperspectral imaging,” Proceedings of the National Academy of Sciences of the United States of America pp. 10 (2011).

Davenport, M.

R. Baraniuk, M. Davenport, R. DeVore, and M. Wakin, “A simple proof of the restricted isometry property for random matrices,” Const. App.28(3), 253–263 (2008).
[CrossRef]

DeVore, R.

R. Baraniuk, M. Davenport, R. DeVore, and M. Wakin, “A simple proof of the restricted isometry property for random matrices,” Const. App.28(3), 253–263 (2008).
[CrossRef]

Donoho, D.

D. Donoho, “Compressed sensing,” IEEE Trans. Inform. Theory.52(4), 1289–1306 (2006).
[CrossRef]

Eldol, J.

B. R. Renikuntla, H. C. Rose, J. Eldol, A. S. Waggoner, and B. A. Armitage, “Improved photostability and fluorescence properties through polyfluorination of a cyanine dye,” Organic. Lett.6(6), 909–912 (2004).
[CrossRef]

Estrada, F.

R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk, “Frequency-tuned salient region detection,” IEEE International Conference on Computer Vision and Pattern Recognitio pp. 1597–1604 (2009).
[CrossRef]

Haase, S.

W. C. Moss, S. Haase, J. M. Lyle, D. A. Agard, and J. W. Sedat, “A novel 3d wavelet-based filter for visualizing features in noisy biological data,” J. Microscopy219, 43–49 (2005).
[CrossRef]

Haugland, R. P.

N. Panchuk-Voloshina, R. P. Haugland, J. Bishop-Stewart, M. K. Bhalgat, P. J. Millard, F. Mao, W. Leung, and R. P. Haugland, “Alexa dyes, a series of new fluorescent dyes that yield exceptionally bright, photostable conjugates,” J. Histochem. Cytochem.47, 1179–1188 (1999).
[CrossRef] [PubMed]

N. Panchuk-Voloshina, R. P. Haugland, J. Bishop-Stewart, M. K. Bhalgat, P. J. Millard, F. Mao, W. Leung, and R. P. Haugland, “Alexa dyes, a series of new fluorescent dyes that yield exceptionally bright, photostable conjugates,” J. Histochem. Cytochem.47, 1179–1188 (1999).
[CrossRef] [PubMed]

Hemami, S.

R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk, “Frequency-tuned salient region detection,” IEEE International Conference on Computer Vision and Pattern Recognitio pp. 1597–1604 (2009).
[CrossRef]

Hennink, E. J.

L. Song, E. J. Hennink, T. Young, and H. J. Tanke, “Photobleaching kinetics of fluorescein in quantitative fluorescence microscopy,” Biophys. J.68, 2588–2600 (1995).
[CrossRef] [PubMed]

Inoue, S.

S. Inoue and K. R. Spring, Video MicroscopyNew York: Plenum Press13, (1997).
[CrossRef]

Leung, W.

N. Panchuk-Voloshina, R. P. Haugland, J. Bishop-Stewart, M. K. Bhalgat, P. J. Millard, F. Mao, W. Leung, and R. P. Haugland, “Alexa dyes, a series of new fluorescent dyes that yield exceptionally bright, photostable conjugates,” J. Histochem. Cytochem.47, 1179–1188 (1999).
[CrossRef] [PubMed]

Lyle, J. M.

W. C. Moss, S. Haase, J. M. Lyle, D. A. Agard, and J. W. Sedat, “A novel 3d wavelet-based filter for visualizing features in noisy biological data,” J. Microscopy219, 43–49 (2005).
[CrossRef]

Malik, J.

P. Perona and J. Malik, “Scale-space and edge detection using anisotropic diffusion,” IEEE Trans. Pattern. Anal. Mach. Intell.12, 629–639 (1990).
[CrossRef]

Mao, F.

N. Panchuk-Voloshina, R. P. Haugland, J. Bishop-Stewart, M. K. Bhalgat, P. J. Millard, F. Mao, W. Leung, and R. P. Haugland, “Alexa dyes, a series of new fluorescent dyes that yield exceptionally bright, photostable conjugates,” J. Histochem. Cytochem.47, 1179–1188 (1999).
[CrossRef] [PubMed]

Marim, M.

M. Marim and E. Angelini, “Denoising in fluorescence microscopy using compressed sensing with multiple reconstructions and non-local merging,” Eng. Med. Biol. (EMBC), 2010 Annual International Conference of the IEEE3394(7), 3394–3397 (2010).
[CrossRef]

M. Marim, E. Angelini, and J. C. Olivo-Marin, “Compressed sensing in biological microscopy,” in Proc. SPIE Wavelets XIII7446, 3394–3397 (2009).

Masters, B. R.

J. B. Pawley and B. R. Masters, “Handbook of biological confocal microscopy, third edition,” J. Bio-Med. Opt.13(029902), (2008).

Mathies, R. A.

R. A. Mathies, K. Peck, and L. Stryer, “Optimization of high-sensitivity fluorescence detection,” Anal. Chem.62, 1786–1791 (1990).
[CrossRef] [PubMed]

Millard, P. J.

N. Panchuk-Voloshina, R. P. Haugland, J. Bishop-Stewart, M. K. Bhalgat, P. J. Millard, F. Mao, W. Leung, and R. P. Haugland, “Alexa dyes, a series of new fluorescent dyes that yield exceptionally bright, photostable conjugates,” J. Histochem. Cytochem.47, 1179–1188 (1999).
[CrossRef] [PubMed]

Mirza, I. O.

Moss, W. C.

W. C. Moss, S. Haase, J. M. Lyle, D. A. Agard, and J. W. Sedat, “A novel 3d wavelet-based filter for visualizing features in noisy biological data,” J. Microscopy219, 43–49 (2005).
[CrossRef]

Moussavi, H.

V. Studer, J. Bobin, M. Chahid, H. Moussavi, E. J. Candes, and M. Dahan, “Compressive fluorescence microscopy for biological and hyperspectral imaging,” Proceedings of the National Academy of Sciences of the United States of America pp. 10 (2011).

Olivo-Marin, J. C.

M. Marim, E. Angelini, and J. C. Olivo-Marin, “Compressed sensing in biological microscopy,” in Proc. SPIE Wavelets XIII7446, 3394–3397 (2009).

Panchuk-Voloshina, N.

N. Panchuk-Voloshina, R. P. Haugland, J. Bishop-Stewart, M. K. Bhalgat, P. J. Millard, F. Mao, W. Leung, and R. P. Haugland, “Alexa dyes, a series of new fluorescent dyes that yield exceptionally bright, photostable conjugates,” J. Histochem. Cytochem.47, 1179–1188 (1999).
[CrossRef] [PubMed]

Pawley, J. B.

J. B. Pawley and B. R. Masters, “Handbook of biological confocal microscopy, third edition,” J. Bio-Med. Opt.13(029902), (2008).

Peck, K.

R. A. Mathies, K. Peck, and L. Stryer, “Optimization of high-sensitivity fluorescence detection,” Anal. Chem.62, 1786–1791 (1990).
[CrossRef] [PubMed]

Perona, P.

P. Perona and J. Malik, “Scale-space and edge detection using anisotropic diffusion,” IEEE Trans. Pattern. Anal. Mach. Intell.12, 629–639 (1990).
[CrossRef]

Petty, H. R.

H. R. Petty, “Fluorescence microscopy: Established and emerging methods, experimental strategies, and applications in immunology,” Microsc. Res. Tech.70(8), 687–709 (2007).
[CrossRef] [PubMed]

Pierres, A.

S. Sabri, F. Richelme, A. Pierres, A. Benoliel, and P. Bongrand, “Interest of image processing in cell biology and immunology,” J. Immunol. Methods.208, 1–27 (1997).
[CrossRef]

Piper, J.

R. Connally, D. Veal, and J. Piper, “Flash lamp-excited time-resolved fluorescence microscope suppresses autofluorescence in water concentrates to deliver an 11-fold increase in signal-to-noise ratio,” J. Biomed. Opt.9, 725–734 (2004).
[CrossRef] [PubMed]

R. Connally, D. Veal, and J. Piper, “Novel flashlamp based timeresolved fluorescence microscope reduces autofluorescence for 30-fold contrast enhancement in environmental samples,” Proc. SPIE4964, 14–23 (2003).
[CrossRef]

R. Connally, D. Veal, and J. Piper, “High resolution detection of fluorescently labeled microorganisms in environmental samples using time-resolved fluorescence microscopy,” FEMS Microbiol Ecol41, 239–245 (2002).
[CrossRef] [PubMed]

Piston, D.

D. Piston, “Choosing objective lenses: The importance of numerical aperture and magnification in digital microscopy,” The Biological Bulletin195, 1–4 (1998).
[CrossRef] [PubMed]

Prather, D. W.

Renikuntla, B. R.

B. R. Renikuntla, H. C. Rose, J. Eldol, A. S. Waggoner, and B. A. Armitage, “Improved photostability and fluorescence properties through polyfluorination of a cyanine dye,” Organic. Lett.6(6), 909–912 (2004).
[CrossRef]

Richelme, F.

S. Sabri, F. Richelme, A. Pierres, A. Benoliel, and P. Bongrand, “Interest of image processing in cell biology and immunology,” J. Immunol. Methods.208, 1–27 (1997).
[CrossRef]

Romberg, J.

E. Candes and J. Romberg, “Quantitative robust uncertainty principles and optimally sparse decompositions,” Found. Comput. Math.6(2), 227–254 (2006).
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E. Candes, J. Romberg, and T. Tao, “Stable signal recovery from incomplete and inaccurate measurements,” Commun. Pure Appl. Math.59(8), 1207–1221 (2006).
[CrossRef]

J. Romberg, E. Candes, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inform. Theory.52(2), 489–509 (2006).
[CrossRef]

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B. R. Renikuntla, H. C. Rose, J. Eldol, A. S. Waggoner, and B. A. Armitage, “Improved photostability and fluorescence properties through polyfluorination of a cyanine dye,” Organic. Lett.6(6), 909–912 (2004).
[CrossRef]

Sabri, S.

S. Sabri, F. Richelme, A. Pierres, A. Benoliel, and P. Bongrand, “Interest of image processing in cell biology and immunology,” J. Immunol. Methods.208, 1–27 (1997).
[CrossRef]

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S. Schwartz, A. Wong, and D. A. Clausi, “Saliency-guided compressive sensing approach to efficient laser range measurement,” J. Visual Commun. Image Represent. (DOI: http://dx..org/10.1016/j.jvcir.2012.02.002 ), (2012).
[CrossRef]

S. Schwartz, A. Wong, and D. A. Clausi, “Saliency-guided compressive fluorescence microscopy” In 34th Int. Conf. Eng. Med. Biol. (EMBC 2012) (to be published).

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W. C. Moss, S. Haase, J. M. Lyle, D. A. Agard, and J. W. Sedat, “A novel 3d wavelet-based filter for visualizing features in noisy biological data,” J. Microscopy219, 43–49 (2005).
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L. Song, E. J. Hennink, T. Young, and H. J. Tanke, “Photobleaching kinetics of fluorescein in quantitative fluorescence microscopy,” Biophys. J.68, 2588–2600 (1995).
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S. Inoue and K. R. Spring, Video MicroscopyNew York: Plenum Press13, (1997).
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V. Studer, J. Bobin, M. Chahid, H. Moussavi, E. J. Candes, and M. Dahan, “Compressive fluorescence microscopy for biological and hyperspectral imaging,” Proceedings of the National Academy of Sciences of the United States of America pp. 10 (2011).

Susstrunk, S.

R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk, “Frequency-tuned salient region detection,” IEEE International Conference on Computer Vision and Pattern Recognitio pp. 1597–1604 (2009).
[CrossRef]

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L. Song, E. J. Hennink, T. Young, and H. J. Tanke, “Photobleaching kinetics of fluorescein in quantitative fluorescence microscopy,” Biophys. J.68, 2588–2600 (1995).
[CrossRef] [PubMed]

Tao, T.

J. Romberg, E. Candes, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inform. Theory.52(2), 489–509 (2006).
[CrossRef]

E. Candes, J. Romberg, and T. Tao, “Stable signal recovery from incomplete and inaccurate measurements,” Commun. Pure Appl. Math.59(8), 1207–1221 (2006).
[CrossRef]

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A. Beck and M. Teboulle, “Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems,” IEEE Trans. Imag. Proc.18(11), 2419–2434 (2009).
[CrossRef]

A. Beck and M. Teboulle, “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,” SIAM J. Imag. Sci.1, 183–202 (2009).
[CrossRef]

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R. Connally, D. Veal, and J. Piper, “Flash lamp-excited time-resolved fluorescence microscope suppresses autofluorescence in water concentrates to deliver an 11-fold increase in signal-to-noise ratio,” J. Biomed. Opt.9, 725–734 (2004).
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R. Connally, D. Veal, and J. Piper, “Novel flashlamp based timeresolved fluorescence microscope reduces autofluorescence for 30-fold contrast enhancement in environmental samples,” Proc. SPIE4964, 14–23 (2003).
[CrossRef]

R. Connally, D. Veal, and J. Piper, “High resolution detection of fluorescently labeled microorganisms in environmental samples using time-resolved fluorescence microscopy,” FEMS Microbiol Ecol41, 239–245 (2002).
[CrossRef] [PubMed]

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B. R. Renikuntla, H. C. Rose, J. Eldol, A. S. Waggoner, and B. A. Armitage, “Improved photostability and fluorescence properties through polyfluorination of a cyanine dye,” Organic. Lett.6(6), 909–912 (2004).
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R. Baraniuk, M. Davenport, R. DeVore, and M. Wakin, “A simple proof of the restricted isometry property for random matrices,” Const. App.28(3), 253–263 (2008).
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S. Schwartz, A. Wong, and D. A. Clausi, “Saliency-guided compressive sensing approach to efficient laser range measurement,” J. Visual Commun. Image Represent. (DOI: http://dx..org/10.1016/j.jvcir.2012.02.002 ), (2012).
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S. Schwartz, A. Wong, and D. A. Clausi, “Saliency-guided compressive fluorescence microscopy” In 34th Int. Conf. Eng. Med. Biol. (EMBC 2012) (to be published).

Wu, Y.

Ye, P.

Young, T.

L. Song, E. J. Hennink, T. Young, and H. J. Tanke, “Photobleaching kinetics of fluorescein in quantitative fluorescence microscopy,” Biophys. J.68, 2588–2600 (1995).
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J. Zakrzewski, “Integrating a spectrometer with an optical microscope presents challenges,” SPIE Magazine pp. 29 (2003).

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R. A. Mathies, K. Peck, and L. Stryer, “Optimization of high-sensitivity fluorescence detection,” Anal. Chem.62, 1786–1791 (1990).
[CrossRef] [PubMed]

Biophys. J. (1)

L. Song, E. J. Hennink, T. Young, and H. J. Tanke, “Photobleaching kinetics of fluorescein in quantitative fluorescence microscopy,” Biophys. J.68, 2588–2600 (1995).
[CrossRef] [PubMed]

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E. Candes, J. Romberg, and T. Tao, “Stable signal recovery from incomplete and inaccurate measurements,” Commun. Pure Appl. Math.59(8), 1207–1221 (2006).
[CrossRef]

Comptes rendus - Mathematique (1)

E. J. Candes, “Restricted isometry property and its implications for compressed sensing,” Comptes rendus - Mathematique346(9–10), 589–592 (2008).

Const. App. (1)

R. Baraniuk, M. Davenport, R. DeVore, and M. Wakin, “A simple proof of the restricted isometry property for random matrices,” Const. App.28(3), 253–263 (2008).
[CrossRef]

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M. Marim and E. Angelini, “Denoising in fluorescence microscopy using compressed sensing with multiple reconstructions and non-local merging,” Eng. Med. Biol. (EMBC), 2010 Annual International Conference of the IEEE3394(7), 3394–3397 (2010).
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FEMS Microbiol Ecol (1)

R. Connally, D. Veal, and J. Piper, “High resolution detection of fluorescently labeled microorganisms in environmental samples using time-resolved fluorescence microscopy,” FEMS Microbiol Ecol41, 239–245 (2002).
[CrossRef] [PubMed]

Found. Comput. Math. (1)

E. Candes and J. Romberg, “Quantitative robust uncertainty principles and optimally sparse decompositions,” Found. Comput. Math.6(2), 227–254 (2006).
[CrossRef]

IEEE Trans. Imag. Proc. (1)

A. Beck and M. Teboulle, “Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems,” IEEE Trans. Imag. Proc.18(11), 2419–2434 (2009).
[CrossRef]

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D. Donoho, “Compressed sensing,” IEEE Trans. Inform. Theory.52(4), 1289–1306 (2006).
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J. Romberg, E. Candes, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inform. Theory.52(2), 489–509 (2006).
[CrossRef]

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J. B. Pawley and B. R. Masters, “Handbook of biological confocal microscopy, third edition,” J. Bio-Med. Opt.13(029902), (2008).

J. Biomed. Opt. (1)

R. Connally, D. Veal, and J. Piper, “Flash lamp-excited time-resolved fluorescence microscope suppresses autofluorescence in water concentrates to deliver an 11-fold increase in signal-to-noise ratio,” J. Biomed. Opt.9, 725–734 (2004).
[CrossRef] [PubMed]

J. Histochem. Cytochem. (1)

N. Panchuk-Voloshina, R. P. Haugland, J. Bishop-Stewart, M. K. Bhalgat, P. J. Millard, F. Mao, W. Leung, and R. P. Haugland, “Alexa dyes, a series of new fluorescent dyes that yield exceptionally bright, photostable conjugates,” J. Histochem. Cytochem.47, 1179–1188 (1999).
[CrossRef] [PubMed]

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S. Sabri, F. Richelme, A. Pierres, A. Benoliel, and P. Bongrand, “Interest of image processing in cell biology and immunology,” J. Immunol. Methods.208, 1–27 (1997).
[CrossRef]

J. Microscopy (1)

W. C. Moss, S. Haase, J. M. Lyle, D. A. Agard, and J. W. Sedat, “A novel 3d wavelet-based filter for visualizing features in noisy biological data,” J. Microscopy219, 43–49 (2005).
[CrossRef]

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H. R. Petty, “Fluorescence microscopy: Established and emerging methods, experimental strategies, and applications in immunology,” Microsc. Res. Tech.70(8), 687–709 (2007).
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Opt. Express (1)

Organic. Lett. (1)

B. R. Renikuntla, H. C. Rose, J. Eldol, A. S. Waggoner, and B. A. Armitage, “Improved photostability and fluorescence properties through polyfluorination of a cyanine dye,” Organic. Lett.6(6), 909–912 (2004).
[CrossRef]

Proc. SPIE (1)

R. Connally, D. Veal, and J. Piper, “Novel flashlamp based timeresolved fluorescence microscope reduces autofluorescence for 30-fold contrast enhancement in environmental samples,” Proc. SPIE4964, 14–23 (2003).
[CrossRef]

Proc. SPIE Wavelets XIII (1)

M. Marim, E. Angelini, and J. C. Olivo-Marin, “Compressed sensing in biological microscopy,” in Proc. SPIE Wavelets XIII7446, 3394–3397 (2009).

SIAM J. Imag. Sci. (1)

A. Beck and M. Teboulle, “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,” SIAM J. Imag. Sci.1, 183–202 (2009).
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J. Zakrzewski, “Integrating a spectrometer with an optical microscope presents challenges,” SPIE Magazine pp. 29 (2003).

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Other (6)

S. Inoue and K. R. Spring, Video MicroscopyNew York: Plenum Press13, (1997).
[CrossRef]

V. Studer, J. Bobin, M. Chahid, H. Moussavi, E. J. Candes, and M. Dahan, “Compressive fluorescence microscopy for biological and hyperspectral imaging,” Proceedings of the National Academy of Sciences of the United States of America pp. 10 (2011).

M. Riffle and T. N. Davis, “The Yeast Resource Center Public Image Repository: A large database of fluorescence microscopy images,” http://images.yeastrc.org/imagerepo/searchImageRepoInit.do .

S. Schwartz, A. Wong, and D. A. Clausi, “Saliency-guided compressive fluorescence microscopy” In 34th Int. Conf. Eng. Med. Biol. (EMBC 2012) (to be published).

S. Schwartz, A. Wong, and D. A. Clausi, “Saliency-guided compressive sensing approach to efficient laser range measurement,” J. Visual Commun. Image Represent. (DOI: http://dx..org/10.1016/j.jvcir.2012.02.002 ), (2012).
[CrossRef]

R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk, “Frequency-tuned salient region detection,” IEEE International Conference on Computer Vision and Pattern Recognitio pp. 1597–1604 (2009).
[CrossRef]

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Figures (12)

Fig. 1
Fig. 1

SNR vs. compression rate for fluorescence microscopy measurements contaminated by Gaussian noise with standard deviation of 3% and were the learning is performed by 1%, 5% and 10%

Fig. 2
Fig. 2

Example fluorescence microscopy image used for testing (ID 12): (a) Fully sampled data, (b) Noisy measurements (standard deviation = 3%) (c) Noisy measurements (standard deviation = 5.5%), (d) Noisy measurements (standard deviation = 7%)

Fig. 3
Fig. 3

Example fluorescence microscopy data used for testing (ID 5): (a) Fully sampled data, (b) Noisy measurements (standard deviation = 5.5%)

Fig. 4
Fig. 4

Example fluorescence microscopy measurement image used for testing. Original fully sampled real noisy fluorescence microscopy measurements: (a) ID 8565, (b) ID 3499, (c) ID 5352

Fig. 5
Fig. 5

SNR vs. noise levels with different ensembles

Fig. 6
Fig. 6

SNR vs. noise level at 75% compression rate and ensemble size of 10

Fig. 7
Fig. 7

SNR vs. compression rate for fluorescence microscopy measurements contaminated by Gaussian noise with standard deviation of 3%

Fig. 8
Fig. 8

Image ID: 64 with synthetic noise: (a) FCFM reconstruction at 75% compression rate and 3% noise level, (b) SSREF reconstruction at 75% compression rate and 3% noise level, (c) FCFM reconstruction at 75% compression rate and 5.5% noise level, (d) SSREF reconstruction at 75% compression rate and 5.5% noise level

Fig. 9
Fig. 9

Image ID: 5 with synthetic noise: (a) FCFM reconstruction at 60% compression rate and 3% noise level, (b) SSREF reconstruction at 60% compression rate and 3% noise level, (c) FCFM reconstruction at 65% compression rate and 5.5% noise level, (d) SSREF reconstruction at 65% compression rate and 5.5% noise level

Fig. 10
Fig. 10

Image ID: 8565: (a) FCFM at 84% compression rate, (b) SSREF at 84% compression rate

Fig. 11
Fig. 11

Image ID: 3499: (a) FCFM at 85% compression rate, (b) SSREF at 85% compression rate

Fig. 12
Fig. 12

Image ID: 5352: (a) FCFM at 78% compression rate, (b) SSREF at 78% compression rate

Equations (16)

Equations on this page are rendered with MathJax. Learn more.

Ω M × N = { ( m , n ) | m = 0 , , M 1 , n = 0 , , N 1 }
Γ ( m , n ) = { 1 , if ( m , n ) Ω D 0 , if ( m , n ) Ω D
Ω M × N = Ω D Ω S Ω D S c , with Ω D Ω S Ω D S c =
y k = f , φ k + e k = m = 0 M 1 n = 0 N 1 f ( m , n ) φ k ( m , n ) + e k
φ k Q ( m , n ) = { φ k D ( m , n ) , if ( m , n ) Ω D φ k S ( m , n ) , if ( m , n ) Ω S 0 , if ( m , n ) Ω D S c
y k Q = f , φ k Q + e k , k = 1 , 2 , , K .
p D ( x | μ , σ ) = 𝒩 ( x | μ , σ D 2 ) , if ( m , n ) Ω D
p S ( x | π , σ S ) = π α ( x ) + ( 1 π ) 𝒩 ( x | μ , σ S 2 ) , if ( m , n ) ( Ω D S c Ω S )
f ˜ = E { f t ¯ } , t = 1 , 2 , T
Γ ( m , n ) = 1 , if S ( m , n ) > τ , ( m , n )
S ( m , n ) = I μ I ( m , n )
p D = 𝒩 ( x | 0 , 1 ) , if ( m , n ) Ω D
p S = 0.9 α ( x ) + 0.1 𝒩 ( x | 0 , 1 ) , if ( m , n ) ( Ω D S c Ω S ) ,
arg min f { λ f T V l 1 + 1 2 Φ f ¯ y ¯ 2 2 }
x T V l 1 = i = 1 m 1 j = 1 n 1 { | x i , j x i + 1 , j | + | x i , j x i , j + 1 | } , x m × n
x 2 = i = 1 n x i 2

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