Automated image segmentation for detecting cell spreading for metastasizing assessments of cancer development

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The automated segmentation of cells in microscopic images is an open research problem that has important implications for studies of the developmental and cancer processes based on in vitro models. In this paper, we present the approach for segmentation of the DIC images of cultured cells using G-neighbor smoothing followed by Kauwahara filtering and local standard deviation approach for boundary detection. NIH FIJI/ImageJ tools are used to create the ground truth dataset. The results of this work indicate that detection of cell boundaries using segmentation approach even in the case of realistic measurement conditions is a challenging problem.

Original languageEnglish
Title of host publication2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2382-2387
Number of pages6
Volume2017-January
ISBN (Electronic)9781509063673
DOIs
Publication statusPublished - Nov 30 2017
Event2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 - Manipal, Mangalore, India
Duration: Sep 13 2017Sep 16 2017

Conference

Conference2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
CountryIndia
CityManipal, Mangalore
Period9/13/179/16/17

Fingerprint

Image segmentation
Cells

Keywords

  • Cancer
  • G-neighbor
  • Image processing
  • Live cell imaging
  • Microscopy

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

Cite this

Kauanova, S., Vorobjev, I., & James, A. P. (2017). Automated image segmentation for detecting cell spreading for metastasizing assessments of cancer development. In 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 (Vol. 2017-January, pp. 2382-2387). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACCI.2017.8126203

Automated image segmentation for detecting cell spreading for metastasizing assessments of cancer development. / Kauanova, Sholpan; Vorobjev, Ivan; James, Alex Pappachen.

2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 2382-2387.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kauanova, S, Vorobjev, I & James, AP 2017, Automated image segmentation for detecting cell spreading for metastasizing assessments of cancer development. in 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 2382-2387, 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, Manipal, Mangalore, India, 9/13/17. https://doi.org/10.1109/ICACCI.2017.8126203
Kauanova S, Vorobjev I, James AP. Automated image segmentation for detecting cell spreading for metastasizing assessments of cancer development. In 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. Vol. 2017-January. Institute of Electrical and Electronics Engineers Inc. 2017. p. 2382-2387 https://doi.org/10.1109/ICACCI.2017.8126203
Kauanova, Sholpan ; Vorobjev, Ivan ; James, Alex Pappachen. / Automated image segmentation for detecting cell spreading for metastasizing assessments of cancer development. 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. pp. 2382-2387
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