Skip to main content

Automated Segmentation and Computation of the Leukocytes Based on Morphological Operator

  • Conference paper
  • First Online:
International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018 (ICICI 2018)

Abstract

Cell image segmentation becomes important and yet difficult task in quantitative cytopathology. The main objective is to develop an algorithm to segment and calculate the amount of neutrophils using morphological operators. The current work focuses on extraction of neutrophils from the peripheral blood smear was taken and it’s stained using Leishman stain to obtain differential leukocyte count. The particle analysis is done by extorting the edges to isolate the appropriate elements from the surrounding image after suitable thresholding technique. The preliminary results in this study reveals the potentials of using particle analysis method in cell image segmentation for automation and further used for classifying.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Swedlow, J.R., Eliceiri, K.W.: Open source bioimage informatics for cell biology. Trends Cell Biol. 19(11), 656–660 (2009)

    Article  Google Scholar 

  2. Rittscher, J.: Characterization of biological processes through automated image analysis. Annu. Rev. Biomed. Eng. 12, 315–344 (2010)

    Article  Google Scholar 

  3. Peng, H.: Bioimage informatics: a new area of engineering biology. Bioinformatics 24(17), 1827–1836 (2008)

    Article  Google Scholar 

  4. Adollah, R., Mashor, M.Y., Nasir, N.M., Rosline, H., Mahsin, H., Adilah, H.: Blood cell image segmentation: a review. In: 4th Kuala Lumpur International Conference on Biomedical Engineering 2008, pp. 141–144. Springer, Berlin, Heidelberg (2008)

    Google Scholar 

  5. Comaniciu, D., Meer, P.: Cell image segmentation for diagnostic pathology. In: Advanced Algorithmic Approaches to Medical Image Segmentation, pp. 541–558. Springer, London (2002)

    Chapter  Google Scholar 

  6. Bengtsson, E., Wahlby, C., Lindblad, J.: Robust cell image segmentation methods. Pattern Recogn. Image Anal. 14(2), 157–167 (2004)

    Google Scholar 

  7. Singh, S., Kumar, D.: Red & green blood vessel extraction from the retinal images. IJARCCE, 4(6), June 2015

    Article  Google Scholar 

  8. Mohammed, E.A., Mohamed, M.M.A., Naugler, C., Far, B.H.: Chronic Lymphocytic Leukemia cell segmentation from microscopic blood images using watershed algorithm and optimal Thresholding. In: IEEE International Conference on CCECE 2013 (2013)

    Google Scholar 

  9. Meijering, Erik: Cell segmentation: 50 years down the road. IEEE Signal Process. Mag. 29(5), 140–145 (2012)

    Article  Google Scholar 

  10. Forsberg, D., Monsef, N.: Evaluating cell nuclei segmentation for use on whole-slide images in lung cytology. In: IEEE International Conference on Pattern Recognition (2014)

    Google Scholar 

  11. Wu, Q., Merchant, F.A., Castleman, K.R.: Microscope Image Processing. Academic Press, Burlington (2008)

    Google Scholar 

  12. Klinger, T.: Image processing with Lab VIEW and IMAQ Vision. Prentice Hall Professional, Upper Saddle Rive (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to B. Geethanjali .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Vijay Mani Shankar, L., Mahesh, V., Geethanjali, B., Subashini, R. (2019). Automated Segmentation and Computation of the Leukocytes Based on Morphological Operator. In: Hemanth, J., Fernando, X., Lafata, P., Baig, Z. (eds) International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018. ICICI 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-030-03146-6_84

Download citation

Publish with us

Policies and ethics