CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Segmentation of Trophectoderm in Microscopic Images of Human Embryos using Watershed Method

by Somashekar Aloor, Geeta Hanji
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Number 3
Year of Publication: 2016
Authors: Somashekar Aloor, Geeta Hanji
10.5120/ijca2016910441

Somashekar Aloor, Geeta Hanji . Segmentation of Trophectoderm in Microscopic Images of Human Embryos using Watershed Method. International Journal of Computer Applications. 145, 3 ( Jul 2016), 34-40. DOI=10.5120/ijca2016910441

@article{ 10.5120/ijca2016910441,
author = { Somashekar Aloor, Geeta Hanji },
title = { Segmentation of Trophectoderm in Microscopic Images of Human Embryos using Watershed Method },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 145 },
number = { 3 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 34-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume145/number3/25260-2016910441/ },
doi = { 10.5120/ijca2016910441 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:47:48.760257+05:30
%A Somashekar Aloor
%A Geeta Hanji
%T Segmentation of Trophectoderm in Microscopic Images of Human Embryos using Watershed Method
%J International Journal of Computer Applications
%@ 0975-8887
%V 145
%N 3
%P 34-40
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Work presented through this paper aims at performing the optimization of IVF treatment. Considering the vital aspect that helps in accurate analysis of embryo viability, in this regard many embryo scoring techniques have been reported in the literature. The usual way of analysing the quality of human embryo is through the grading process (that is on the day fifth of embryo development) that takes into consideration the following components along with their morphological features; namely: zona pellucid, trophectoderm and inner cell mass (ICM). Hatching of embryo to the uterus wall mainly depend on trophectoderm (TE) region development. Thus the quality assessment of TE region in order to find the viable embryo is highly essential. This paper present a method for TE region segmentation using watershed method, so that the segmented region is represented in much better way. These results of segments are compared with those obtained level-set algorithm and meaningful conclusions have been derived.

References
  1. Edwards, R. G., Steptoe and P. C., “Current status of in-vitro fertilization and implantationof human embryos,” The Lancet 2. pp. 1265-1269, 1983.
  2. J. G. Bromer and E. Seli, “Assessment of embryo viability in assisted reproductive technologies: Shortcomings of current approaches and the emerging role of metabolomics,” Curr. Opin. Obstet. Gynecol., vol. 20, pp. 234–241, 2008.
  3. D. K. Gardner and W. B. Schoolcraft, “In-vitro culture of human blastocyst, R Jansen, D Mortimer (Eds.),” Towards Reproductive Certainty: Infertility Genetics Beyond, Parthenon Press, Carnforth. pp. 378–388, 1999.
  4. P.Crosignani, “Multiple gestation pregnancy,” Towards Reproductive Certainty Infertility Genetics Beyond, vol. 15, no. 7, pp. 1856–1864, 2000.
  5. A. Ahlstr¨om, C. Westin, E. Reismer, M. Wikland, and T. Hardarson, “Trophectoderm morphology: An important parameter for predicting live birth after single blastocyst tran,” Human Reproduction, vol. 26, no. 12, pp. 3289–3296, 2011.
  6. A. E. B. Bendus, J. F. Mayer, S. K. Shipley, and W. H. Catherino, “Interobserver and intraobserver variation in day 3 embryo grading,” Fertility Sterility, vol. 86, no. 6, pp. 1608–1615, 2006.
  7. C. Hnida, E. Engenheiro, and S. Ziebe, “Computer-controlled, multilevel, morphometric analysis of blastomere size as biomarker of fragmentation and multinuclearity in human embryos,” Human Reproduction, vol. 19, no. 2, pp. 288–293, 2004.
  8. A. Giusti, G. Corani, L. Gambardella, C. Magli, and L. Gianaroli, “Blastomere segmentation and 3D morphology measurements of early embryos fromHoffmanmodulation contrast image stacks,” in Proc. IEEE Int. Conf. Biomed. Imag., From NanoMacro, 2010, pp. 1261–1264.
  9. C. Li, C. Xu, C. Gui, and M. D. Fox, “Level set evolution without reinitialization: A new variational formulation,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis Pattern Recog., 2005, vol. 1, pp. 430–436.
  10. J.-M. Morel, A. B. Petro, and C. Sbert, “A PDE formalization of retinex theory,” IEEE Trans. Image Process., vol. 19, no. 11, pp. 2825–2837, Nov. 2010.
  11. C. Li, R. Huang, Z. Ding, J. Gatenby, N. Metaxas, and J. Gore, “A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI,” IEEE Trans. Image Process., vol. 20, no. 7, pp. 2007–2016, Jul. 2011.
  12. D. K. Gardner, E. Surrey, D. Minjarez, A. Leitz, J. Stevens, and W. B. Schoolcraft, “Single blastocyst transfer: A prospective randomized trial,” Fertility Sterility, vol. 81, no. 3, pp. 551–555, 2004.
  13. J. Cohen, R. F. Simons, R. G. Edwards, C. B. Fehilly, and S. B. Fishel, “Pregnancies following the frozen storage of expanding human blastocysts,” J. In Vitro Fertilization Embryo Transfer, vol. 2, no. 2, pp. 59–64, 1985.
  14. A. Dokras, I. Sargent, and D. Barlow, “Human blastocyst grading: An indicator of developmental potential?” Human Reproduction, vol. 8, no. 12, pp. 2119–2127, 1993.
  15. U. D. Pedersen, O. F. Olsen, and N. H. Olsen, “A multiphase variational level set approach for modelling human embryos,” in Proc. 2nd IEEE Workshop Variational Geometric Level Set Methods Comput. Vis., 2003, pp. 25–32.
  16. H. K. Zhao, T. Chan, B. Merriman, and S. Osher, “A variational level set approach to multiphase motion,” J. Comput. Phys., vol. 127, no. 1, pp. 179–195, 1996.
  17. A. Karlsson, N. C. Overgaard, and A. Heyden, “A two-step area based method for automatic tight segmentation of zona pellucida in HMC images of human embryos,” in Proc. 5th Int. Conf. Scale Space PDE Methods Comput. Vis., 2005, pp. 503–514.
  18. D. Morales, E. Bengoetxea, and P. Larraaga, “Automatic segmentation of zona pellucida in human embryo images applying an active contour model,” in Proc. Med. Image Understanding Anal., 2008, pp. 209–213.
  19. J. Canny, “A computational approach to edge detection,” IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-8, no. 6, pp. 679–698, Nov. 1986.
  20. C. Wong, K. Loewke, N. Bossert, B. Behr, C. De Jonge, T. Baer, and R. Reijo Pera, “Non-invasive imaging of human embryos before embryonic genome activation predicts development to the blastocyst stage,” in Nat. Biotechnol., vol. 28, no. 10, 2010, pp. 1115–21.
  21. E. Santos Filho, J. A. Noble, andD.Wells, “Toward a method for automatic grading of microscope human embryo images,” in Proc. IEEE Int. Symp. Biomed. Imag., From NanoMacro, 2010, pp. 1289–1292.
  22. E. H. Land and J. J. McCann, “Lightness and retinex theory,” J. Opt. Soc. Am., vol. 61, no. 1, pp. 1–11, 1971.
  23. V. Agarwal, B. Abidi, A. Koschan, and M. Abidi, “An overview of color constancy algorithms,” J. Pattern Recog. Res., vol. 1, no. 1, pp. 42–54, 2006.
  24. E. Provenzi, L. de Carli, A. Rizzi, and D. Marini, “Mathematical definition and analysis of the Retinex algorithm,” vol. 22, no. 12, pp. 2613–2621, 2005.
  25. L. Lei, Y. Zhou, and J. Li, “An investigation of Retinex algorithms for image enhancement,” J. Electron. (China), vol. 24, no. 5, pp. 696–700, 2007.
  26. D. H. Brainard and B. A. Wandell, “Analysis of the Retinex theory of color vision,” J. Opt. Soc. Am. A, vol. 3, no. 10, pp. 1651–1661, 1986.
  27. T. G. Stockham, “Image processing in the context of a visual model,” Proc. IEEE, vol. 60, no. 7, pp. 828–842, Jul. 1972.
  28. J. Frankle, and J.McCann, “Method and apparatus for lightness imaging,” U.S. Patent 4 384 336, May 17, 1983.
  29. B. Funt, F. Ciurea, and J.Mccann, “Retinex in Matlab,” J. Electron. Imag., vol. 13, no. 1, pp. 48–57, Jan. 2004.
  30. B. K. Horn, “Determining Lightness from an image,” Comput. Graph. Image Process., vol. 3, no. 1, pp. 277–299, 1974.
  31. Lamia Jaafar Belaid, Walid Mourou, “Image Segmentation: A Watershed Transformation Agorithm,” Image segmentation, 2009.
  32. D. McKeown, T. Bulwinkle, S. Cochran, W. Harvey, C. McGlone, and J. Shufelt, “Performance evaluation for automatic feature extraction,” Int. Archives Photogrammetry Remote Sens., vol. 33, pp. 379–394, 2000.
  33. Canner S.j, Lefiervre L, Hughes DC, Barrat CL, “Cracking the egg: Increased complexity in the zona pellucida,” Human Reproduction,vol. 20(5), pp. 1148-1152, 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Grading of Blastocyst In vitro fertilization (IVF) Level set Retinex Watershed K-means Clustering .

Powered by PhDFocusTM