Abstract
Cell and particle quantification is one of the frequently used techniques in biology and clinical study. Variations of cell/particle population and/or protein expression level can provide information on many biological processes. In this chapter, we propose an image-based automatic quantification approach that can be applied to images from both fluorescence and electron microscopy. The algorithm uses local maxima to identify labelling targets and uses watershed segmentation to define their boundaries. The method is able to provide information on size, intensity centroids and average intensity within the labelling partitions. Further developed from this method, we demonstrated its applications in four different research projects, including recruitment enumeration of circulating T cell in non-lymphoid tissues, cell clustering in the early development of the chick embryo, gold particle localization and clustering in electron microscopy, and registration/co-localization of transcription factors in neural tube development of early chick embryo. The advantages and limitations of the method are also discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aune MW, Sandberg S. (2000) Automated counting of white and red blood cells in the cerebrospinal fluid. Clin Lab Hematol 22, 203–10.
Sims AJ, Bennett MK, Murray A. (2002) Comparison of semi-automated image analysis and manual methods for tissue quantification in pancreatic carcinoma. Phys Med Biol 47, 1255–66.
Agarwal A, Sharma RK. (2007) Automation is the key to standardized semen analysis using the automated SQA-V sperm quality analyzer. Fertil Steril 87, 156–62.
Barthmaier P. (2003) Microfluidic technology applied to protein sizing and quantization. Technical Proceedings of the 2003 Nanotechnology Conference and Trade Show 1, 67–9.
Li X, Tibbe AGJ, Droog E, Terstappen LWMM, Greve J. (2007) An immunomagnetic single-platform image cytometer for cell enumeration based on antibody specificity. Clin Vaccine Immunol 14, 412–9.
Benali A, Leefken I, Eysel UT, Weiler E. (2003) A computerized image analysis system for quantitative analysis of cells in histological brain sections. J Neurosci Methods 125, 33–43.
Steinera GE, Eckera RC, Kramera G, Stockenhuber F, Marberger MJ. (2000) Automated data acquisition by confocal laser scanning microscopy and image analysis of triple stained immunofluorescent leukocytes in tissue. J Immunol Methods 237, 39–50.
Wahlby C, Sintor IM, Erlandsson NF, Borgefors G, Bengtsson E. (2004) Combining intensity, edge and shape information for 2D and 3D segmentation of cell nuclei in tissue sections. J Microsc 215, 67–76.
Oritiz de Solorzano C, Garcia Rodriguez E, Jones A, Pinkel D, Gray J, Sudar D, Lockett S. (1999) Segmentation of confocal microscope images of cell nuclei in thick tissue sections. J Microsc 193, 212–26.
Canny J. (1986) A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell PAMI-8, 679–98.
Adams R, Bischof L. (1994) Seeded region growing. IEEE Trans Pattern Anal Mach Intell 16, 641–47.
Meyer F, Beucher S. (1990) Morphological segmentation. J Vis Commun Image Represent 1, 21–46.
Chalana V, Winter TC III, Cyr DR, Haynor DR, Kim Y. (1996) Automatic fetal head measurements from sonographic images. Acad Radiol 3, 628–35.
Cosıo FA, Flores JAM, Castaneda MAP, Solano S, Tato P. (2005) Automatic analysis of immunocytochemically stained tissue samples. Med Biol Eng Comput 43, 672–77.
Mat-Isa NA, Mashor MY, Othman NH. (2005) Seeded region growing features extraction algorithm; its potential use in improving screening for cervical cancer. Int J Comput Internet Manage 13, 61–70.
Shimada T, Katoa K, Kamikouchi A, Itoa K. (2005) Analysis of the distribution of the brain cells of the fruit fly by an automatic cell counting algorithm. Physica A 350, 144–9.
Bernard R, Kanduser M, Pernu F. (2001) Model-based automated detection of mammalian cell colonies. Phys Med Biol 46, 3061–72.
Forero MG, Cristobal G, Desco M. (2006) Automatic identification of Mycobacterium tuberculosis by Gaussian mixture models. J Microsc 223, 120–32.
Shorte SL, Frischknecht F. (2007) Imaging Cellular and Molecular Biological Functions. Berlin, Heidelberg: Springer-Verlag, 407–21.
Vincent L, Soille P. (1991) Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Trans Pattern Anal Mach Intell 3, 583–98.
Roerdink JBTM, Meijster A. (2001) The watershed transform: definitions, algorithms and parallelization strategies. Fundam Informaticae 41, 187–228.
Mirenda V, Jarmin SJ, David R, Dyson J, Scott D, Yan Gu Y, Lechler RI, Okkenhaug K, Marelli-Berg FM. (2007) Physiologic and aberrant regulation of memory T-cell trafficking by the costimulatory molecule CD28. Blood 109, 2968–77.
James MJ, Belaramani L, Prodromidou K, Datta A, Nourshargh S, Lombardi G, Dyson J, Scott D, Simpson E, Cardozo L, Warrens A, Szydlo RM, Lechler RI, Marelli-Berg FM. (2003) Anergic T cells exert antigen-independent inhibition of cell–cell interactions via chemokine metabolism. Blood 102, 2173–9.
Itasaki N, Bel-Vialar S, Krumlauf R. (1999) ‘Shocking’ developments in chick embryology: electroporation and in ovo gene expression. Nat Cell Biol 1, E203–7.
Xie SQ, Pombo A. (2006) Distribution of different phosphorylated forms of RNA polymerase II in relation to Cajal and PML bodies in human cells: an ultrastructural study. Histochem Cell Biol 125, 21–31.
Hamburger V, Hamilton HL. (1951) A series of normal stages in the development of the chick embryo. J Morphol 88, 49–92.
Ericson J, Rashbass P, Schedl A, Brenner-Morton S, Kawakami A, van Heyningen V, Jessell TM, Briscoe J. (1997) Pax6 controls progenitor cell identity and neuronal fate in response to graded Shh signaling. Cell 90, 169–80.
Novitch BG, Chen AI, Jessell TM. (2001) Coordinate regulation of motor neuron subtype identity and pan-neuronal properties by the bHLH repressor Olig2. Neuron 31, 773–89.
Serpente P, Tumpel S, Ghyselinck NB, Niederreither K, Wiedemann LM, Dolle P, Chambon P, Krumlauf R, Gould AP. (2005) Direct crossregulation between retinoic acid receptor band Hox genes during hindbrain segmentation. Development 132, 503–13.
Sanchez-Marin FJ. (1999) Automatic segmentation of contours of corneal cells. Comput Biol Med 29, 243–58.
Thomann D, Rines DR, Sorger PK, Danuser G. (2002) Automatic fluorescent tag detection in 3D with super-resolution: application to the analysis of chromosome movement. J Microsc 208, 49–64.
Dessaud E, Yang LL, Hill K, Cox B, Ulloa F, Ribeiro A, Mynett A, Novitch BG, Briscoe J. (2007) Interpretation of the sonic hedgehog morphogen gradient by a temporal adaptation mechanism. Nature 450, 717–21.
Jarmin SJ, David R, Ma L, Chai J, Dewchand H, Takesono A, Ridley AJ, Okkenhaug K, Marelli-Berg FM. (2008) T cell receptor-induced phosphoinositide-3-kinase p110δ activity is required for T cell localization to antigenic tissue in mice. J Clin Invest 118, 1154–64.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Zhu, D. et al. (2010). Applying an Adaptive Watershed to the Tissue Cell Quantification During T-Cell Migration and Embryonic Development. In: Marelli-Berg, F., Nourshargh, S. (eds) T-Cell Trafficking. Methods in Molecular Biology, vol 616. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-461-6_14
Download citation
DOI: https://doi.org/10.1007/978-1-60761-461-6_14
Published:
Publisher Name: Humana Press, Totowa, NJ
Print ISBN: 978-1-60761-460-9
Online ISBN: 978-1-60761-461-6
eBook Packages: Springer Protocols