Literature Cited

  • 1
    Allalou A,Wählby C. BlobFinder, a tool for fluorescence microscopy image cytometry. Comput Methods Programs Biomed 2009; 94: 5865.
  • 2
    Vidal F,Bello F,Brodlies KW,John NW,Gould D,Phillips R,Avis NJ. Principles and applications of computer graphics in medicine. Comp Graphics Forum 2006; 25: 113137.
  • 3
    Wittenberg T,Becher F,Hensel M,Steckhan D. Image segmentation of cell nuclei based on classification in the color space. In: Vander Sloten J,Verdonck P,Nyssen M,Haueisen J, editors. 4th European Conference of the International Federation for Medical and Biological Engineering (ECIFMBE), Vol 22/1; November 23–27, 2008; Antwerp, Belgium. Berlin: Springer; 2008. pp 613614.
  • 4
    Srinivasa G. Active Mask Framework for Segmentation of Fluorescence Microscope Images. Pittsburgh: Carnegie-Mellon University; 2008.
  • 5
    Wang Q,Niemi J,Tan CM,You L,West M. Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy. Cytometry A J Int Soc Anal Cytol 2010; 77: 101110.
  • 6
    Romanelli M,Buitelaar P,Sintek M. Modeling linguistic facets of multimedia content for semantic annotation. In: Falcidieno B,Spagnuolo M,Avrithis Y,Kompatsiaris I,Buitelaar P, editors. Semantic Multimedia: Second International Conference on Semantic and Digital Media Technologies (SAMT); December 5–7, 2007; Genoa, Italy. Berlin: Springer; 2007. pp 240251.
  • 7
    Garbay C. Computer vision: A plea for a constructivist view. In: Combi C,Shahar Y,Abu-Hanna A, editors. Artificial Intelligence in Medicine: 12th Conference on Artificial Intelligence in Medicine (AIME); July 18–22, 2009; Verona, Italy. Berlin: Springer; 2009. pp 615.
  • 8
    Restif C. Segmentation and evaluation of fluorescence microscopy images [MD Dissertation]. Oxford: Oxford Brookes University; 2006. Available at: http://cms.brookes.; [accessed Oct 2011].
  • 9
    Harder N,Mora-Bermúdez F,Godinez WJ,Ellenberg J,Eils R,Rohr K. Automated analysis of the mitotic phases of human cells in 3D fluorescence microscopy image sequences. Med Image Comput Comput Assist Interv 2006; 9: 840848.
  • 10
    Harder N,Mora-Bermúdez F,Godinez WJ,Ellenberg J,Eils R,Rohr K. Determination of mitotic delays in 3D fluorescence microscopy images of human cells using an error-correcting finite state machine. In: Horsch A,Deserno TM,Handels H,Meinzer HP,Tolxdorff T, editors. Bildverarbeitung für die Medizin 2007: Algorithmen—Systeme—Anwendungen. Proceedings des Workshops vom 25–27. März 2007 in München. Berlin: Springer; 2007. pp 242246.
  • 11
    Venkatraman R,Raman R,Raman B,Moss RB,Rubin GD,Mathers LH,Robinson TE. Fully automated system for three-dimensional bronchial morphology analysis using volumetric multidetector computed tomography of the chest. J Digit Imaging 2006; 19: 132139.
  • 12
    Wittenberg T,Grobe M,Münzenmayer C,Kuziela H,Spinnler K. A semantic approach to segmentation of overlapping objects. Methods Inf Med 2004; 43: 343353.
  • 13
    Otsu N. A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 1979; 9: 6266.
  • 14
    Nandy K,Gudla PR,Meaburn KJ,Misteli T,Lockett SJ. Automatic nuclei segmentation and spatial FISH analysis for cancer detection. Conf Proc IEEE Eng Med Biol Soc 2009; 2009: 67186721.
  • 15
    Du X,Dua S. Segmentation of fluorescence microscopy cell images using unsupervised mining. Open Med Inform J 2010; 4: 4149.
  • 16
    Malpica N,de Solórzano CO,Vaquero JJ,Santos A,Vallcorba I,García-Sagredo JM,del Pozo F. Applying watershed algorithms to the segmentation of clustered nuclei. Cytometry 1997; 28: 289297.
  • 17
    Wählby C,Lindblad J,Vondrus M,Begtsson E,Björkesten L. Algorithms for cytoplasm segmentation of fluorescence labelled cells. Anal Cell Pathol 2002; 24: 101111.
  • 18
    Lindblad J,Wählby C,Bengtsson E,Zaltsman A Image analysis for automatic segmentation of cytoplasms and classification of Rac1 activation. Cytometry A J Int Soc Anal Cytol 2004; 57: 2233.
  • 19
    Zhu D,Jarmin S,Ribeiro A,Prin F,Xie SQ,Sullivan K,Briscoe J,Gould AP,Marelli-Berg FM,Gu Y. Applying an adaptive watershed to the tissue cell quantification during T-cell migration and embryonic development. Methods Mol Biol 2010; 616: 207228.
  • 20
    Soille P. Morphological Image Analysis: Principles and Applications. Berlin: Springer; 1999.
  • 21
    Metzler V,Bienert H,Lehmann T,Mottaghy K,Spitzer K. A novel method for quantifying shape deformation applied to biocompatibility testing. ASAIO J 1999; 45: 264271.
  • 22
    Metzler V,Lehmann T,Bienert H,Mottaghy K,Spitzer K. Scale-independent shape analysis for quantitative cytology using mathematical morphology. Comput Biol Med 2000; 30: 135151.
  • 23
    Zhang G,Jia X,Pham T,Crane D. Multistage spatial property based segmentation for quantification of fluorescence distribution in cells. In: Pham T,Zhou X, editors. 2009 International Symposium on Computational Models for Life Sciences (CMLS); July 28–29, 2009; Sofia, Bulgaria. Berlin: Springer; 2010. pp 312. ( American Institute of Physics Conference Proceedings, Vol. 1210.)
  • 24
    Srinivasa G,Fickus M,Kovacevic J. Active contour-based multiresolution transforms for the segmentation of fluorescence microscope images. In: Van De Ville D,Goyal VK,Papadakis M, editors. Wavelets XII; August 26–29, 2007; San Diego, California. Bellingham, WA: Society of Photo-optical Instrumentation Engineers (SPIE); 2007. pp 254261. ( Proceedings of SPIE—The International Society for Optical Engineering, Vol. 6701.)
  • 25
    Srinivasa G,Fickus MC,Guo Y,Linstedt AD,Kovacević J. Active mask segmentation of fluorescence microscope images. IEEE Trans Image Process 2009; 18: 18171829.
  • 26
    Möller B,Gress O,Stöhr N,Hüttelmaier S,Posch S. Adaptive segmentation of cells and particles in fluorescent microscope images. In: Richard P,Braz J, editors. Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP), Vol. 2; May 17–21, 2010; Angers, France. Berlin: Springer; 2010. pp 97106.
  • 27
    Ersoy I,Bunyak F,Chagin V,Cardoso MC,Palaniappan K. Segmentation and classification of cell cycle phases in fluorescence imaging. Lect Notes Comput Sci 2009; 5762: 617624.
  • 28
    Yu W,Lee H,Hariharan S,Bu W,Ahmed S. Quantitative neurite outgrowth measurement based on image segmentation with topological dependence. Cytometry A J Int Soc Anal Cytol 2009; 75: 289297.
  • 29
    Yu W,Lee H,Hariharan S,Bu W,Ahmed S. Evolving generalized Voronoi diagrams for accurate cellular image segmentation. Cytometry A J Int Soc Anal Cytol 2010; 77: 379386.
  • 30
    Cheng J,Rajapakse JC. Segmentation of clustered nuclei with shape markers and marking function. IEEE Trans Biomed Eng 2009; 56: 741748.
  • 31
    Dzyubachyk O,Essers J,van Cappellen WA,Baldeyron C,Inagaki A,Niessen WJ,Meijering E. Automated analysis of time-lapse fluorescence microscopy images: From live cell images to intracellular foci. Bioinformatics 2010; 26: 24242430.
  • 32
    Dzyubachyk O,van Cappellen WA.Essers J.Niessen WJ,Meijering E. Advanced level-set-based cell tracking in time-lapse fluorescence microscopy. IEEE Trans Med Imaging 2010; 29: 852867. Erratum in: IEEE Trans Med Imaging 2010; 29: 1331.
  • 33
    Nattkemper TW. A neural network-based system for high throughput fluorescence micrograph evaluation [MD dissertation]. Bielefeld, Germany: University of Bielefeld, Faculty of Technology; 2001.
  • 34
    Nattkemper TW,Twellmann T,Ritter H,Schubert W. Human vs machine: Evaluation of fluorescence micrographs. Comput Biol Med 2003; 33: 3143.
  • 35
    Nattkemper TW,Wersing H,Schubert W,Ritter H. A neural network architecture for automatic segmentation of fluorescence micrographs. In: Verleysen M, editor. 8th European Symposium on Artificial Neural Networks; April 26–28, 2000; Bruges. Brussels: D Facto Publications; 2000. pp 177182.
  • 36
    Wang M,Zhou X,Li F,Huckins J,King RW,Wong ST. Novel cell segmentation and online SVM for cell cycle phase identification in automated microscopy. Bioinformatics 2008; 24: 94101.
  • 37
    Coelho LP,Shariff A,Murphy RF. Nuclear segmentation in microscope cell images: A hand-segmented dataset and comparison of algorithms. Proc IEEE Int Symp Biomed Imaging 2009; 5193098: 518521.
  • 38
    Roerdink J,Meijster A. The watershed transform: Definitions, algorithms and parallelization strategies. Fundam Inf 2001; 41: 187228.
  • 39
    Elter M,Daum V,Wittenberg T. Maximum-intensity-linking for segmentation of fluorescence-stained cells. In: Metaxas DN,Whitaker RT,Rittscher J,Sebastian TB, editors. Proceedings of 1st Workshop on Microscopic Image Analysis with Applications in Biology (in conjunction with MICCAI); October 5, 2006; Copenhagen. Copenhagen: MIAAB; 2006. pp 4649. Available at: [accessed Oct 2011].
  • 40
    Habeler G,Natter K,Thallinger GG,Crawford ME,Kohlwein SD,Trajanoski Z. YPL.db: The yeast protein localization database. Nucleic Acids Res 2002; 30: 8083.
  • 41
    Kals M,Natter K,Thallinger GG,Trajanoski Z,Kohlwein SD. YPL.db2: The yeast protein localization database, version 2.0. Yeast 2005; 22: 213218.
  • 42
    Riffle M,Davis TN. The yeast resource center public image repository: A large database of fluorescence microscopy images. BMC Bioinformatics 2010; 11: 263.
  • 43
    Singh AK,Manjunath BS,Murphy RF. A distributed database for biomolecular images. SIGMOD Rec 2004; 33: 6571. Available at:; [accessed Oct 2011].
  • 44
    Frenkel-Morgenstern M,Cohen AA,Geva-Zatorsky N,Eden E,Prilusky J,Issaeva I,Sigal A,Cohen-Saidon C,Liron Y,Cohen L,Danon T,Perzov N,Alon U. Dynamic proteomics: A database for dynamics and localizations of endogenous fluorescently-tagged proteins in living human cells. Nucleic Acids Res 2010; 38: D508D512.
  • 45
    Serra J. Image Analysis and Mathematical Morphology. London: Academic Press; 1982.
  • 46
    Hartigan J,Wong M. A k-means clustering algorithm. Appl Stat 1979; 28: 100108.
  • 47
    Goldberg DE. Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley; 1989.
  • 48
    Wall M. A C++ Library of Genetic Algorithm Components. Cambridge, MA: Massachusetts Institute of Technology; 1996. Available at: 2.4.7). [accessed Oct 2011].
  • 49
    Rojas Dominguez A,Nandi AK. Improved dynamic-programming-based algorithms for segmentation of masses in mammograms. Med Phys 2007; 34: 42564269.