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[1]
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Al-Awadhi, F.
Statistical image analysis and confocal microscopy.
PhD thesis, Department of Mathematical Sciences, University of Bath,
Bath, UK, 2001.
Keywords: statistical inference, confocal microscopy, structure extraction, 3d microscopy
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[2]
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Al-Awadhi, F., Jennison, C., and Hurn, M.
Statistical image analysis for a confocal microscopy two-dimensional
section of cartilage growth.
Journal of the Royal Statistical Society: Applied Statistics
53, 1 (2004), 31-49.
[ PDF ]
Keywords: statistical inference, confocal microscopy, structure extraction
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[3]
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Al-Kofahi, K. A., Can, A., Lasek, S., Szarowski, D. H., Dowell-Mesfin, N.,
Shain, W., Turner, J. N., and Roysam, B.
Median-based robust algorithms for tracing neurons from noisy
confocal microscope images.
IEEE Transactions on Information Technology in Biomedicine 7, 4
(December 2003), 302-317.
[ PDF ]
Keywords: confocal microscopy, structure extraction
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[4]
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Al-Kofahi, K. A., Lasek, S., Szarowski, D. H., Pace, C. J., Nage, G.,
Turner, J. N., and Roysam, B.
Rapid automated 3d tracing of neurons from confocal image stacks.
IEEE Transactions on Information Technology in Biomedicine 6, 2
(June 2002), 171-187.
[ PDF ]
Keywords: confocal microscopy, structure extraction
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[5]
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Allen, M. T., Prusinkiewicz, P., and DeJong, T. M.
Using L-systems for modeling sourceink interactions, architecture
and physiology of growing trees: the L-PEACH model.
New Phytologist 166, 3 (2005), 869 - 880.
[ PDF ]
Keywords: l-system
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[6]
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Amenta, N., and Bern, M.
Surface reconstruction by Voronoi filtering.
Discrete and Computational Geometry 22 (1999), 481-504.
[ PDF |
Notes ]
Keywords: surface reconstruction
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[7]
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Amenta, N., Bern, M., and Kamvysselis, M.
A new Voronoi-based surface reconstruction algorithm.
In SIGGRAPH 1998: Proceedings of the conference on computer
graphics and interactive techniques (1998), pp. 415-421.
[ PDF |
Notes ]
Keywords: surface reconstruction
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[8]
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Amenta, N., and Kil, Y. J.
Defining point-set surfaces.
In SIGGRAPH 2004: Proceedings of the conference on computer
graphics and interactive techniques (2004), vol. 23, pp. 264-270.
[ PDF |
Notes ]
Keywords: surface reconstruction
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[9]
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Andrieu, C., de Freitas, N., Doucet, A., and Jordan, M. I.
An introduction to MCMC for machine learning.
Machine Learning 50, 1 (2003), 5-43.
[ PDF ]
Keywords: machine learning, statistical inference, markov chain monte carlo sampling
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[10]
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Barbu, A., and Zhu, S.-C.
Generalizing Swendsen-Wang to sampling arbitrary posterior
probabilities.
IEEE Transactions on Pattern Analysis and Machine Intelligence
27, 8 (2005), 1239-1253.
[ PDF ]
Keywords: statistical inference, swendsen-wang sampling
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[11]
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Belichenko, P. V., and Dahlström, A.
Confocal laser scanning microscopy and 3d reconstructions of neuronal
structures in human brain cortex.
NeuroImage 2, 3 (September 1995), 201-207.
[ PDF ]
Keywords: confocal microscopy, structure extraction
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[12]
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Bishop, C. M.
Pattern recognition and machine learning.
Springer, 2006.
Keywords: pattern recognition, machine learning
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[13]
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Boxall, E. S., White, N. S., and Benham, G. S.
The processing of three-dimensional confocal data sets.
In Multidimensional microscopy, P. C. Cheng, T. H. Lin, W. L.
Wu, and J. L. Wu, Eds. Springer-Verlag, 1994.
Keywords: 3d microscopy
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[14]
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Can, A., Shen, H., Turner, J. N., Tanenbaum, H. L., and Roysam, B.
Rapid automated tracing and feature extraction from retinal fundus
images using direct exploratory algorithms.
IEEE Transactions on Information Technology in Biomedicine 3, 2
(June 1999), 125-138.
[ PDF ]
Keywords: microscopy, structure extraction
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[15]
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Canny, J.
A computational approach to edge detection.
IEEE Transactions on Pattern Analysis and Machine
Intelligence 8 (1986), 679-698.
Keywords: image analysis, edge detection
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[16]
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Carasso, A. S.
Direct blind deconvolution.
SIAM Journal on Applied Mathematics 61, 6 (2001), 1980-2007.
[ PDF ]
Keywords: blind deconvolution
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[17]
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Casella, G., and Robert, C. P.
Rao-blackwellisation of sampling schemes.
Biometrika 83, 1 (1996), 81-94.
[ PDF ]
Keywords: rao-blackwellization, markov chain monte carlo sampling
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[18]
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Chen, H., Swedlow, J. R., Grote, M., Sedat, J. W., and Agard, D. A.
The collection, processing, and display of digital three-dimensional
images of biological specimens.
In Handbook of biological confocal microscopy, J. B. Pawley,
Ed. Plenum Press, New York, NY, 1995, pp. 197-210.
Keywords: 3d microscopy
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[19]
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Cheng, P. C., Lin, T. H., Wu, W. L., and Wu, J. L., Eds.
Multidimensional microscopy.
Springer-Verlag, 1994.
Keywords: 3d microscopy
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[20]
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Conchello, J.
Superresolution and convergence properties of the
expectation-maximization algorithm for maximum-likelihood deconvolution of
incoherent images.
Journal of Optical Society of America A 15, 10 (1998),
2609-2619.
[ PDF ]
Keywords: deconvolution
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[21]
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Conchello, J., and Hanson, E. W.
Enhanced 3-d reconstruction from confocal scanning microscope images.
I: Deterministic and maximum likelihood reconstructions.
Applied Optics 29, 26 (1990), 3795-3804.
[ PDF ]
Keywords: confocal microscopy, deconvolution, 3d microscopy
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[22]
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Conchello, J., Kim, J. J., and Hanson, E. W.
Enhanced three-dimensional reconstruction from confocal scanning
microscope images. II: Depth discrimination versus signal-to-noise
ratio in partially confocal images.
Applied Optics 33, 17 (1994), 3740-3750.
[ PDF ]
Keywords: confocal microscopy, deconvolution, 3d microscopy
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[23]
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Conn, P. M., Ed.
Confocal microscopy, vol. 307 of Methods in enzymology.
Academic Press, San Diego, CA, 1999.
Keywords: confocal microscopy
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[24]
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Deussen, O., Hanrahan, P., Lintermann, B., Měch, R., Pharr, M., and
Prusinkiewicz, P.
Realistic modeling and rendering of plant ecosystems.
In SIGGRAPH 1998: Proceedings of the conference on computer
graphics and interactive techniques (New York, NY, USA, 1998), ACM Press,
pp. 275-286.
[ PDF ]
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[25]
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Escuela, G., Ochoa, G., and Krasnogor, N.
Evolving L-Systems to capture protein structure native
conformations, 1 ed., vol. Volume 3447/2005 of Lecture Notes in
Computer Science.
Springer-Verlag, New York NY, 2005, pp. 74-84.
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[26]
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Fellner, D. W., and Helmberg, C.
Robust rendering of general ellipses and elliptical arcs.
ACM Transactions on Graphics 12, 3 (1993), 251-276.
Keywords: computer graphics, ellipses
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[27]
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Fleishman, S., Cohen-Or, D., and Silva, C. T.
Robust moving least-squares fitting with sharp features.
In SIGGRAPH 2005: Proceedings of the conference on computer
graphics and interactive techniques (2005), vol. 24, pp. 544-552.
[ PDF |
Notes ]
Keywords: surface reconstruction
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[28]
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Geman, S., and Geman, D.
Stochastic relaxation, Gibbs distributions, and the Bayesian
restoration of images.
IEEE Transactions on Pattern Analysis and Machine Intelligence
6 (1984), 721-741.
Keywords: statistical inference, markov chain monte carlo sampling, gibbs sampling
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[29]
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Green, P. J.
Reversible jump Markov chain Monte Carlo computation and
Bayesian model determination.
Biometrika 82, 4 (1995), 711-732.
[ PDF ]
Keywords: statistical inference, reversible jump markov chain monte carlo sampling
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[30]
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Gui-ting, L., Yu-zhen, Q., Peng, Z., Wei-hua, D., Yuan-ming, Q., and
Hong-tao, G.
Etiological role of alternaria alternata in human esophageal
cancer.
Chin Medical Journal 105, 5 (1992), 394-400.
Keywords: Alternaria, cancer
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[31]
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Hammel, M., Prusinkiewicz, P., Remphrey, W., and Davidson, C.
Simulating the development of fraxinus pennsylvanica shoots using
L-systems.
In Sixth Western Computer Graphics Symposium (1995),
pp. 49-58.
Keywords: l-system
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[32]
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Han, F., and Zhu, S.-C.
Bottom-up/top-down image parsing by attribute graph grammar.
In International Conference on Computer Vision (2005),
vol. 2, pp. 1778-1785.
[ PDF ]
Keywords: object recognition, statistical grammar inference
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[33]
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Hastie, T., Tibshirani, R., and Friedman, J.
The elements of statistical learning.
Springer, 2006.
Keywords: pattern recognition, machine learning
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[34]
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Hastings, W. K.
Monte Carlo sampling methods using Markov chains and their
applications.
Biometrika 57 (1970), 97-109.
Keywords: markov chain monte carlo sampling
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[35]
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Holmes, T. J.
Expectation-maximization restoration of band-limited, truncated
point-process intensities with application in microscopy.
Journal of Optical Society of America A 6, 7 (1989),
1006-1014.
[ PDF ]
Keywords: deconvolution, microscopy
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[36]
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Holmes, T. J.
Blind deconvolution of quantum-limited incoherent imagery:
maximum-likelihood approach.
Journal of Optical Society of America A 9 (1992), 1052-1061.
[ PDF ]
Keywords: blind deconvolution
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[37]
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Holmes, T. J., Bhattacharyya, S., Cooper, J. A., Hanzel, D.,
Krishnamurthi, V., Lin, W., Roysam, B., Szarowski, D. H., and Turner, J. N.
Light microscopic images reconstructed by maximum likelihood
deconvolution.
In Handbook of biological confocal microscopy, J. B. Pawley,
Ed. Plenum Press, New York, NY, 1995, pp. 389-402.
Keywords: deconvolution, microscopy
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[38]
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Holmes, T. J., and O'connor, N. J.
Blind deconvolution of 3d transmitted light brightfield micrographs.
Journal of Microscopy 200, 2 (November 2000), 114-127.
[ PDF ]
Keywords: blind deconvolution, 3d microscopy
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[39]
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Hong, S., and Pryor, B.
Development of selective media for the isolation and enumeration of
alternaria species from soil and plant debris.
Canadian Journal of Microbiology 59, 7 (2004), 461-468.
[ PDF ]
Keywords: Alternaria
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[40]
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Hoppe, H., DeRose, T., Duchamp, T., Halstead, M., Jin, H., McDonald, J.,
Schweitzer, J., and Stuetzle, W.
Piecewise smooth surface reconstruction.
In SIGGRAPH 1994: Proceedings of the conference on computer
graphics and interactive techniques (1994), pp. 295-302.
[ PDF ]
Keywords: surface reconstruction
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[41]
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Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., and Stuetzle, W.
Surface reconstruction from unorganized points.
In SIGGRAPH 1992: Proceedings of the conference on computer
graphics and interactive techniques (1992), pp. 71-78.
[ PDF ]
Keywords: surface reconstruction
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[42]
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Ioffe, S., and Forsyth, D.
Human tracking with mixtures of trees.
In International Conference on Computer Vision (2001),
vol. 1, pp. 690-695.
[ PDF ]
Keywords: computer vision, machine learning
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[43]
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Kaess, M., Zboinski, R., and Dellaert, F.
MCMC-based multiview reconstruction of piecewise smooth
subdivision curves with a variable number of control points.
In Lecture Notes in Computer Science (2004), vol. 3023,
pp. 329-341.
[ PDF ]
Keywords: rao-blackwellization, markov chain monte carlo sampling
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[44]
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Kirkpatrick, S., Gelatt, C. D., and Vecchi, M. P.
Optimization by simulated annealing.
Science 220, 4598 (1983), 671-680.
Keywords: markov chain monte carlo sampling, simulated annealing
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[45]
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Kong, S. K., Ko, S., Lee, C. Y., and Lui, P. Y.
Practical considerations in acquiring biological signals from
confocal microscope.
In Confocal microscopy, P. M. Conn, Ed., vol. 307 of
Methods in enzymology. Academic Press, San Diego, CA, 1999, pp. 20-26.
Keywords: confocal microscopy
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[46]
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Lindenmayer, A.
Mathematical models for cellular interaction in development, parts i
and ii.
Journal of Theoretical Biology 18, 3 (1968), 280-299,
300-315.
[ PDF ]
Keywords: l-system
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[47]
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Lindenmayer, A.
Developmental systems without cellular interactions, their languages
and grammars.
Journal of Theoretical Biology 30, 3 (1971), 455-484.
[ PDF ]
Keywords: l-system
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[48]
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Lindenmayer, A.
Developmental algorithms for multicellular organisms: A survey of
L-systems.
Journal of Theoretical Biology 54, 1 (1975), 3-22.
Keywords: l-system
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[49]
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Manning, C. D., and Schutze, H.
Foundations of statistical natural language processing.
The MIT Press, 1999.
Keywords: probabilistic context free grammar
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[50]
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Manning, C. D., and Schutze, H.
Foundations of statistical natural language processing.
The MIT Press, 1999, ch. 11, pp. 381-405.
[ PDF ]
Keywords: probabilistic context free grammar
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[51]
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Markham, J., and Conchello, J.
Fast maximum-likelihood image-restoration algorithms for
threedimensional fluorescence microscopy.
Journal of Optical Society of America A 18, 5 (2001),
1062-1071.
[ PDF ]
Keywords: 3d microscopy, deconvolution
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[52]
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McNally, J. G., and Conchello, J.
XCOSM: computational optical sectioning microscopy algorithms.
Software available at http://www.essrl.wustl.edu/ preza/xcosm.
Keywords: 3d microscopy, deconvolution
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[53]
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Meila, M., and Jordan, M. I.
Learning with mixtures of trees.
Journal of Machine Learning Research 1 (2000), 1-48.
[ PDF ]
Keywords: machine learning, mixture model
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[54]
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Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., and
Teller, E.
Equations of state calculations by fast computing machines.
Journal of Chemical Physics 21 (1953), 1087-1092.
Keywords: markov chain monte carlo sampling
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[55]
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Neal, R. M.
Probabilistic inference using Markov chain Monte Carlo methods.
Tech. Rep. CRG-TR-93-1, University of Toronto, 1993.
[ .ps.gz ]
Keywords: statistical inference, markov chain monte carlo sampling
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[56]
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Oppenheimer, P. E.
Real time design and animation of fractal plants and trees.
In SIGGRAPH 1986: Proceedings of the conference on computer
graphics and interactive techniques (New York, NY, USA, 1986), ACM Press,
pp. 55-64.
[ PDF ]
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[57]
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Pawley, J. B., Ed.
Handbook of biological confocal microscopy.
Plenum Press, New York, NY, 1995.
Keywords: confocal microscopy
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[58]
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Preza, C., and Conchello, J.
Depth-variant maximum-likelihood restoration for three-dimensional
fluorescence microscopy.
Journal of Optical Society of America A 21, 9 (2004),
1593-1601.
[ PDF ]
Keywords: 3d microscopy, deconvolution
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[59]
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Prusinkiewicz, P., Lindenmayer, A., and Hanan, J.
Development models of herbaceous plants for computer imagery
purposes.
In SIGGRAPH 1988: Proceedings of the conference on computer
graphics and interactive techniques (New York, NY, USA, 1988), ACM Press,
pp. 141-150.
[ PDF ]
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[60]
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Prusinkiewicz, P., Lindenmayer, A., and Hanan, J., Eds.
The algorithmic beauty of plants.
Springer-Verlag, 1990.
Keywords: computer graphics, l-system
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[61]
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Samal, A., Peterson, B., and Holliday, D. J.
Recognition of plants using a stochastic L-system model.
Journal of Electronic Imaging 11, 1 (2002), 50-58.
[ PDF ]
Keywords: object recognition, stochastic l-system
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[62]
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Samarabandu, J. K., Acharya, R., and Cheng, P.-c.
Analysis and presentation of three dimensional data sets.
In Multidimensional microscopy, P. C. Cheng, T. H. Lin, W. L.
Wu, and J. L. Wu, Eds. Springer-Verlag, 1994.
Keywords: 3d microscopy
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[63]
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Schlecht, J., Barnard, K., and Pryor, B.
Statistical inference of biological structure and point spread
functions in 3D microscopy.
In Proceedings of the Third International Symposium on 3D Data
Processing, Visualization and Transmission (June 2006), pp. 373-380.
[ PDF ]
Keywords: object recognition, machine learning, statistical inference, data-driven markov chain monte carlo sampling
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[64]
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Schlecht, J., Barnard, K., Spriggs, E., and Pryor, B.
Inferring grammar-based structure models in 3D microscopy data.
In IEEE Computer Society Conference on Computer Vision and
Pattern Recognition (June 2007), pp. 1-8.
[ PDF ]
Keywords: object recognition, machine learning, statistical inference, data-driven markov chain monte carlo sampling
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[65]
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Shaw, P. J., and Rawlins, D. J.
The point-spread function of a confocal microscope: its measurement
and use in deconvolution of 3-d data.
Journal of Microscopy 163, 2 (1991), 151-165.
Keywords: confocal microscopy, 3d microscopy, deconvolution, point spread function
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[66]
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Simmons, E.
Alternaria themes and variations 287-304: Species on
caryophyllaceae.
Mycotaxon 70 (1999), 325-369.
Keywords: Alternaria
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[67]
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Song, M., Haralick, R. M., Sheehan, F. H., and Johnson, R. K.
Integrated surface model optimization for freehand three-dimensional
echocardiography.
IEEE Transactions on Medical Imaging 21, 9 (September 2002),
1077-1090.
[ PDF ]
Keywords: statistical inference, machine learning, 3d imaging
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[68]
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Spencer-Phillips, P. T. N., Willey, N., and Johnston, M. A.
Topology: a novel method to describe branching patterns in
peronospora viciae colonies.
Mycological Research 107, 10 (2003), 1123-1131.
Keywords: l-system
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[69]
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Thomma, B.
Alternaria spp.: from general saprophyte to specific parasite.
Molecular Plant Pathology 4, 4 (2003), 225.
[ PDF ]
Keywords: alternaria
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[70]
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Travis, A. J., Hirst, D. J., and Chesson, A.
Automatic classification of plant cells according to tissue using
anatomical features obtained by distance transform.
Annals of Botany 78 (1996), 325-331.
[ PDF ]
Keywords: classification, machine learning
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[71]
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Tu, Z., Chen, X., Yuille, A. L., and Zhu, S.-C.
Image parsing: unifying segmentation, detection, and recognition.
Internation Journal of Computer Vision 63, 2 (2005), 113-140.
[ PDF ]
Keywords: image segmentation, object recognition, machine learning, statistical inference, data-driven markov chain monte carlo sampling
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[72]
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Tu, Z., Zhu, S.-C., and Shum, H.
Image segmentation by data-driven Markov chain Monte Carlo.
IEEE Transactions on Pattern Analysis and Machine Intelligence
24, 5 (2002), 657-673.
[ PDF ]
Keywords: image segmentation, machine learning, statistical inference, data-driven markov chain monte carlo sampling
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[73]
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Webb, R. H.
Theoretical basis of confocal microscopy.
In Confocal microscopy, P. M. Conn, Ed., vol. 307 of
Methods in enzymology. Academic Press, San Diego, CA, 1999, pp. 3-20.
Keywords: confocal microscopy
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[74]
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Weber, J., and Penn, J.
Creation and rendering of realistic trees.
In SIGGRAPH 1995: Proceedings of the conference on computer
graphics and interactive techniques (New York, NY, USA, 1995), ACM Press,
pp. 119-128.
[ PDF ]
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[75]
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Wilken-Jensen, K., and Gravesen, S.
Atlas of moulds in Europe causing respiratory allergy.
ASK Publishing, Copenhagen, Denmark, 1984.
Keywords: Alternaria, allergens
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[76]
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Wilson, C., and Wisniewski, M.
Biological control of postharvest diseases: theory and
practice.
CRC Press Inc., Boca Raton, Fla., 1994.
Keywords: Alternaria, alternata
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[77]
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Zhu, S.-C., Zhang, R., and Tu, Z.
Integrating top-down/bottom-up for object recognition by data driven
Markov chain Monte Carlo.
In Computer Vision and Pattern Recognition (2000).
[ PDF ]
Keywords: object recognition, machine learning, statistical inference, data-driven markov chain monte carlo sampling
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