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

Sholpan Kauanova; Ivan Vorobjev; Alex Pappachen James

doi:10.1109/ICACCI.2017.8126203

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

Sholpan Kauanova, Ivan Vorobjev, Alex Pappachen James

School of Engineering and Digital Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

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 language	English
Title of host publication	2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2382-2387
Number of pages	6
Volume	2017-January
ISBN (Electronic)	9781509063673
DOIs	https://doi.org/10.1109/ICACCI.2017.8126203
Publication status	Published - Nov 30 2017
Event	2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 - Manipal, Mangalore, India Duration: Sep 13 2017 → Sep 16 2017

Conference

Conference	2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
Country/Territory	India
City	Manipal, Mangalore
Period	9/13/17 → 9/16/17

Keywords

Cancer
G-neighbor
Image processing
Live cell imaging
Microscopy

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Information Systems

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10.1109/ICACCI.2017.8126203

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 proceeding › Conference 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

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

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