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Cell Lineage Construction of Neural Progenitor Cells

by N. Jayalakshmi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 90 - Number 4
Year of Publication: 2014
Authors: N. Jayalakshmi
10.5120/15565-4370

N. Jayalakshmi . Cell Lineage Construction of Neural Progenitor Cells. International Journal of Computer Applications. 90, 4 ( March 2014), 40-47. DOI=10.5120/15565-4370

@article{ 10.5120/15565-4370,
author = { N. Jayalakshmi },
title = { Cell Lineage Construction of Neural Progenitor Cells },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 90 },
number = { 4 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 40-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume90/number4/15565-4370/ },
doi = { 10.5120/15565-4370 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:10:12.833005+05:30
%A N. Jayalakshmi
%T Cell Lineage Construction of Neural Progenitor Cells
%J International Journal of Computer Applications
%@ 0975-8887
%V 90
%N 4
%P 40-47
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This study aims at automatic construction of cell lineage from time-lapse images of progenitor cells. In order to construct the cell lineage it is very useful to have an efficient cell tracking system. In this paper we have described a system for tracking neural progenitor cells in a sequence of images using multiple matching object method based on modified mahalanobis algorithm. This system produces the results including the position, shape, motility and ancestry of each cell in every frame, which helps in construction of cell lineage. The proposed method has been implemented to the sequence of image frames and the computational results of cell tracking are presented.

References
  1. Meijering. E, Dzyubachyk. O, Smal. I and Van Cappellen. W. A. Tracking in Cell and Developmental Biology. Seminars in Cell and Developmental Biology, vol. 20, no. 8, pp. 894-902, October 2009.
  2. Gahrton G and Bjorkstrand B. Progress in haemotopoietic stem cell transplantation for multiple myeloma. Journal of Internal Medicine, vol. 248(3), pp. 185-201, 2000.
  3. Singec I, Jandial R, Chain A, Nikkhah G and Snyder EY. The leading edge of stemcell therapeutics. Annu. Rev. Medicine 58: 313-328, 2007.
  4. Stem-cell Therapy: Promise and Reality, Consumer reports on health 17. 6 (2005): 8-9 Academic Search Premier EBSCO. web 5. Apr 2010.
  5. Sulston JE and Horvitz HR. Post embryonic cell lineages of the nematode Caenorhabditis elegans. Developmental Biology, vol. 56, pp. 110-56, 1977.
  6. Sulston JE and Horovitz HR. Abnormal cell lineages in mutans of the nematode Caenorhabditis elegans, Developmental Biology, vol. 82, pp. 41-55, 1981.
  7. Chalfie R, Horvitz HR, Sulston JE, Mutations that lead to reiterations in the cell lineages of C. elegans, Cell, vol. 24, pp. 59-69, 1981.
  8. Omar Al-Kofahi, Richard J. Radke, Susan K. Goderie, Qin Shen, Sally Temple and Badrinath Roysam. Automated cell lineage construction: A Rapid method to Analyze Clonal Development established with Murine Neural Progenitor Cells. Cell Cycle, Vol. 5, No. 3, pp. 327-335, 2006.
  9. Amalka Pinidiyaarachchi and Carolina Wahlby. Seeded watershed for combined segmentation and tracking of cells. ICIAP-2005 proceeding, pp. 336-343, 2005.
  10. Degerman. J, Faijerson. J, Althoff. K, Thorlin. T, Rodriguez. J. H, and Gustavsson. T. A comparative study between Level set and Watershed image segmentation for tracking stem cells in Time-Lapse Microscopy. MIAAB 06, pp. 1-6, 2006.
  11. Nezamoddin N. Kachouie, Paul Fiehguth and Eric Jervis. Stem Cell Localization: A Deconvolution problem. Proceedings of the 29t Annual International Conference of the IEE EMBS City International, France, pp. 5525-5528, 2007.
  12. Chunming Tang and Ewert Bengtsson. Segmentation and Tracking of Neural Stem Cell. Advances in Intelligent Computing, pp. 851-859, 2005.
  13. Dorini. L. B, Minetto. R and Leite. N. J. White Blood Cell Segmentation using morphological operatorsand Scale-Space analysis. Computer Graphics and Image Processing, pp. 294-304, 2007.
  14. Cecilia D. Ruberto, Andrew Dempster, Shahid Khan and Bill Jarra. Segmentation of Blood images using morphological operators. ICPR '00, Vol. 3, 2000.
  15. Langan. D. A, Modestino. J. W, and Zhang. J. Cluster Validation for unsupervised stochastic model based image segmentation. IEEE transaction on Image processing, vol. 7(2), pp. 180-95, 1998.
  16. Theodoros Mouroutis. A. A. B and Stephen J. Roberts. Robust Cell nuclei segmentation using statistical modeling. Journal of Bioimaging, vol. 6(2), pp. 79-91, 1998.
  17. Kittler. J and Illingsworth. J. Minimum Error Thresholding. Pattern Recognition, vol. 19, no. 1, pp. 41-47, 1986.
  18. Otsu. N. A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, vol. 9, no. 1, pp. 62-66, 1979.
  19. Wu. K, Gauthier. D, and Levine. M. Live cell image segmentation. IEEE Transactions onBiomedical Engineering, vol. 42, no . 1, pp. 1-12, 1995.
  20. Markiewicz. T, Osowski. S, Moszczyshki. L, and Satat. R. Myelogeneous leukemia cell image preprocessing or feature generation. 5t International Workshop on Computational Methods in Electrical Engineering, pp. 70-73, 2003.
  21. Vincent. L. and Soille, P. Watersheds in digital spaces: an efficient algorithm based onimmersion simulations. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 13(6), pp. 583 - 598, Jun 1991.
  22. Comaniciu. D and Meer. P. Cell image segmentation for Diagnostic Pathology, Advanced Algorithmic approaches to medical image segmentation: State-of-art applications in cardiology, neurology, mammography nd pathology. Springer 2001, pp. 541-558.
  23. Geusebroek. J. M, Smeulders. A. W. M and Cornelissen. F. Segmentation of cell clusters by nearest neighbour graphs. Proceedings of the third annual conference of the advanced school of computing and Imaging. pp. 248-252, 1997.
  24. Meas-Yedid. V, Cloppet. F, Roumier. A, Alcover. A, Olivo-Marin. J. C, and Stamon. G. Quantitative microscopic image analysis by active contours. VI 2001 Vision Interface Annual Conference - Medical applications, 2001.
  25. Ryoma Bise, Kang Li and Takeo Kanade. Reliably Tracking partially overlapping Neural stem cells in DIC microscopy image sequences. Proceedings of the MICCAI workshop on the Optical tissue image analysis in microscopy, pp. 67-77, 2009.
  26. Tscherepanow. M, Zollner. F, Hillebrand. M, and Kummert. F. Automatic segmentation of unstained living cells in bright field microscope images. Advances in mass Data analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food industry, pp. 158-172, 2008.
  27. Ilker Ersoy and Kannappan Palaniappan. Multi-feature Contour Evolution for Automatic Live cell Segmentation in Time lapse Imagery. EMBS-2008, Engineering in Medicine and Biology Society, pp. 371-374, 2009.
  28. Braun V, Azevedo RB, Gumbel M, Agapow PM, Leroi AM and Meinzer HP. ALES: Cell lineage analysis and mapping of developmental events. Bioinformatics, vol. 19, pp. 851-8, 2003.
  29. Yasuda T, Bannai H, Onami S, Miyano S and Kitano H. Towards automatic construction of cell lineage of C. elegans from nomarski DIC microscopic images. Genome Inform Ser Workshop, vol. 10, pp. 144-54, 1999.
  30. Wählby C, Sintron IM, Erlandsson F, Borgefors G and Bengtsson E. Combining intensity, edge and shape information for 2D and 3D segmentation of cell nuclei in tissue sections. Journal of Microscopy, vol. 215, pp. 67-76, 2004.
  31. Kirubarajan. T, Barshalom. Y and Pattipati. K. Multi assignment for tracking a number of overlapping objects. IEEE Transactions on Aerospace and Electronics Systems, vol. 37(1), pp. 2-21, 2001.
  32. Blake. A and Isard. M. Active Contours: The application of techniques from graphics, vision, control theory and statistics to visual tracking of shapes in motion. London: Springer, 2000.
  33. Zimmer. C, Labruere. E, Meas-Yedid. V, Guillen. N and Olivo-Marin. J. C. Segmentation and tracking of migrating cells in video microscopy with parametric active contours: a tool for cell based drug testing. IEEE Transactions on Medical Imaging, vol. 21(10), pp. 1212-1221, 2002.
  34. Dufour A, Shinin V, Tajbakhsh S, Guillen-Aghion N, Olivo-Marin JC and Zimmer C. Segmenting and tracking fluorescent cells in dynamic 3-D microscopy with coupled active surfaces. IEEE Trans Image Process 2005; vol. 14, pp. 1396-410.
  35. http://www. landesbioscience. com/journals/cc/supple ment/alkofani. zip referred on 20. 5. 2007.
  36. Serra. J. Image Analysis and Mathematical Morphology. Academic Press, Newyork, NY 1982.
  37. RM. Suresh & N. Jayalakshmi, Quantification and segmentation of progenitor cells in Time-lapse microscopy, International Symposium on Bio computing, NIT, Calicut and Indiana University Purdue University, USA, ACM Portal, 2010.
  38. Soille. P. Morphological Image analysis: Principles and Applications, Springer-Verlag, October 1999.
  39. RM. Suresh & N. Jayalakshmi, Stem cell Detection and Segmentation, International Journal of Bioinformatics, Vol. 2, 2009, 73-75.
  40. RM. Suresh & N. Jayalakshmi, Analysis of segmentation methods for stem cell images, International Journal of Emerging Technologies and Applications, Technology and Sciences, Vol 1. 2009,60-67.
  41. Beucher, S. , and Lantuejoul, C. Use of watersheds in contour detection. In Proc. International Workshop on Image Processing, Real-Time Edge and Motion Detection/Estimation. Rennes, September 1979.
  42. Mehmet Sezgin, Bulent Sankur, Survey over image thresholding techniques and quantitative performance evaluation, Journal of Electronic Imaging 13(1), 2004, 146-165.
  43. RM. Suresh & N. Jayalakshmi, Cell Quantification and Watershed Segmentation in Time Lapse Microscopy, International Conference on Digital Image Processing, Singapore, Proc SPIE Vol. 7546, 2010.
  44. Jayalakshmi. N and R. M. Suresh. RM. Analysis of Segmentation and Tracking Algorithms for Time Lapse Microscopic Progenitor Cell Images. International Conference on Signal and Image Processing, IEEE Xplore, Dec 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Cell lineage mapping image segmentation progenitor cell tracking

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