A Statistical Pixel Intensity Model for Segmentation of Confocal Laser Scanning Microscopy Images

Confocal laser scanning microscopy (CLSM) has been widely used in the life sciences for the characterization of cell processes because it allows the recording of the distribution of fluorescence-tagged macromolecules on a section of the living cell. It is in fact the cornerstone of many molecular transport and interaction quantification techniques where the identification of regions of interest through image segmentation is usually a required step. In many situations, because of the complexity of the recorded cellular structures or because of the amounts of data involved, image segmentation either is too difficult or inefficient to be done by hand and automated segmentation procedures have to be considered. Given the nature of CLSM images, statistical segmentation methodologies appear as natural candidates. In this work we propose a model to be used for statistical unsupervised CLSM image segmentation. The model is derived from the CLSM image formation mechanics and its performance is compared to the existing alternatives. Results show that it provides a much better description of the data on classes characterized by their mean intensity, making it suitable not only for segmentation methodologies with known number of classes but also for use with schemes aiming at the estimation of the number of classes through the application of cluster selection criteria.

[1]  Jorma Rissanen,et al.  The Minimum Description Length Principle in Coding and Modeling , 1998, IEEE Trans. Inf. Theory.

[2]  A. W. Kemp,et al.  Characterizations of a discrete normal distribution , 1997 .

[3]  Anil K. Jain,et al.  Markov Random Field Texture Models , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Chee Sun Won,et al.  Unsupervised segmentation of noisy and textured images using Markov random fields , 1992, CVGIP Graph. Model. Image Process..

[5]  Douglas B. Ehlenberger,et al.  Automated reconstruction of three-dimensional neuronal morphology from laser scanning microscopy images. , 2003, Methods.

[6]  R. Webb,et al.  The Pixelated Image , 1990 .

[7]  P. Verveer,et al.  A comparison of image restoration approaches applied to three‐dimensional confocal and wide‐field fluorescence microscopy , 1999, Journal of microscopy.

[8]  James Sharpe,et al.  3D confocal reconstruction of gene expression in mouse , 2001, Mechanisms of Development.

[9]  G. M. P. VAN KEMPEN,et al.  A quantitative comparison of image restoration methods for confocal microscopy , 1997 .

[10]  Sridhar Lakshmanan,et al.  Simultaneous Parameter Estimation and Segmentation of Gibbs Random Fields Using Simulated Annealing , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  S. Dickson,et al.  Visualisation of mycorrhizal fungal structures and quantification of their surface area and volume using laser scanning confocal microscopy , 1999, Mycorrhiza.

[12]  S. Inoué,et al.  Foundations of Confocal Scanned Imaging in Light Microscopy , 2006 .

[13]  W. Webb,et al.  Mobility measurement by analysis of fluorescence photobleaching recovery kinetics. , 1976, Biophysical journal.

[14]  Robert M Zucker,et al.  Evaluation of confocal microscopy system performance. , 2001, Methods in molecular biology.

[15]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  P. Varga,et al.  Electromagnetic diffraction of light focused through a stratified medium. , 1997, Applied optics.

[17]  Petar M. Djuric,et al.  Unsupervised vector image segmentation by a tree structure-ICM algorithm , 1996, IEEE Trans. Medical Imaging.

[18]  J. Besag.  Spatial Interaction and the Statistical Analysis of Lattice Systems , 1974 .

[19]  Elmar Wahle,et al.  The intranuclear mobility of messenger RNA binding proteins is ATP dependent and temperature sensitive , 2002, The Journal of cell biology.

[20]  R. Dasgupta,et al.  Cauchy Equation on Discrete Domain and Some Characterization Theorems , 1994 .

[21]  H. Akaike.  A new look at the statistical model identification , 1974 .

[22]  J. Paul Robinson,et al.  Automated quantification and reconstruction of collagen matrix from 3D confocal datasets , 2003, Journal of microscopy.

[23]  C. Seidel,et al.  Photobleaching of Fluorescent Dyes under Conditions Used for Single-Molecule Detection:  Evidence of Two-Step Photolysis. , 1998, Analytical chemistry.

[24]  David Tollervey,et al.  Depletion of the Yeast Nuclear Exosome Subunit Rrp6 Results in Accumulation of Polyadenylated RNAs in a Discrete Domain within the Nucleolus , 2007, Molecular and Cellular Biology.

[25]  E. Stelzer.  The Intermediate Optical System of Laser-Scanning Confocal Microscopes , 2006 .

[26]  K. Jalink,et al.  Characterization of sectioning fluorescence microscopy with thin uniform fluorescent layers: Sectioned Imaging Property or SIPcharts , 2005, Journal of microscopy.

[27]  A. Nehorai,et al.  Deconvolution methods for 3-D fluorescence microscopy images , 2006, IEEE Signal Processing Magazine.

[28]  Dimitri Van De Ville,et al.  SUB-RESOLUTION MAXIMUM-LIKELIHOOD BASED LOCALIZATION OF FLUORESCENT NANOPARTICLES IN THREE DIMENSIONS , 2007, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[29]  James B. Pawley,et al.  Points, Pixels, and Gray Levels: Digitizing Image Data , 2006 .

[30]  J. Besag.  On the Statistical Analysis of Dirty Pictures , 1986 .

[31]  M. Fordham,et al.  An evaluation of confocal versus conventional imaging of biological structures by fluorescence light microscopy , 1987, The Journal of cell biology.

[32]  Donald B. Rubin,et al.  Max-imum Likelihood from Incomplete Data , 1972 .

[33]  E. Stelzer,et al.  Photobleaching GFP reveals protein dynamics inside live cells. , 1999, Trends in cell biology.

[34]  Robert H. Webb,et al.  The Pixilated Image , 1995 .

[35]  T. Kiss.  Small Nucleolar RNAs An Abundant Group of Noncoding RNAs with Diverse Cellular Functions , 2002, Cell.

[36]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[37]  Yuval Garini,et al.  Segmentation and analysis of the three‐dimensional redistribution of nuclear components in human mesenchymal stem cells , 2008, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[38]  J. Aubin.  Autofluorescence of viable cultured mammalian cells. , 1979, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.

[39]  Anil K. Jain,et al.  Random field models in image analysis , 1989 .

[40]  T. Misteli,et al.  High mobility of proteins in the mammalian cell nucleus , 2000, Nature.

[41]  G H Ball,et al.  A clustering technique for summarizing multivariate data. , 1967, Behavioral science.

[42]  M. David Egger,et al.  The development of confocal microscopy , 1989, Trends in Neurosciences.

[43]  Donald L. Weaver,et al.  Three-dimensional reconstruction by confocal laser scanning microscopy in routine pathologic specimens of benign and malignant lesions of the human breast , 1997, Histochemistry and Cell Biology.

[44]  S. Gibson,et al.  Experimental test of an analytical model of aberration in an oil-immersion objective lens used in three-dimensional light microscopy. , 1992, Journal of the Optical Society of America. A, Optics and image science.

[45]  J. Zerubia,et al.  Gaussian approximations of fluorescence microscope point-spread function models. , 2007, Applied optics.

[46]  P. Danielsson,et al.  Three-dimensional microscopy using a confocal laser scanning microscope. , 1985, Optics letters.

[47]  M. Unser,et al.  The colored revolution of bioimaging , 2006, IEEE Signal Processing Magazine.

[48]  J. Lippincott-Schwartz,et al.  Studying protein dynamics in living cells , 2001, Nature Reviews Molecular Cell Biology.

[49]  James B. Pawley,et al.  Fundamental Limits in Confocal Microscopy , 2006 .

[50]  M. Bear,et al.  Regulation of distinct AMPA receptor phosphorylation sites during bidirectional synaptic plasticity , 2000, Nature.

[51]  Maria Carmo-Fonseca,et al.  The Spinal Muscular Atrophy Disease Gene Product, Smn , 1999, The Journal of cell biology.

[52]  R. Singer,et al.  Localization of ASH1 mRNA particles in living yeast. , 1998, Molecular cell.

[53]  S. Hell,et al.  Aberrations in confocal fluorescence microscopy induced by mismatches in refractive index , 1993 .

[54]  M. Fordham,et al.  Use of confocal imaging in the study of biological structures. , 1987, Applied optics.

[55]  D. M. Shotton,et al.  Confocal scanning optical microscopy and its applications for biological specimens , 1989 .

[56]  David Tollervey,et al.  Inactivation of cleavage factor I components Rna14p and Rna15p induces sequestration of small nucleolar ribonucleoproteins at discrete sites in the nucleus. , 2008, Molecular biology of the cell.