Quantitative characterization for lymphocyte deformation in image sequences

DOI

10.2991/iccnce.2013.154How to use a DOI?

Keywords

Cell deformation characterization, image sequences analysis, cell image analysis, Fourier descriptors, quantitative characterization.

Abstract

A new method is proposed to quantitatively characterize lymphocyte deformation in image sequences. The whole framework includes three steps?cell segmentation, cell tracking, and cell deformation characterization. Firstly, morphological image processing is implemented as a kind of segmentation method to detect cell region. Then, method based on Fourier descriptors is presented to optimize cell contour, which makes cell contour smooth and closer to real contour. Secondly, gradient vector flow (GVF) Snake algorithm is carried out for tracking cell region in image sequences. Finally, the part of cell deformation characterization is accomplished by improved symmetry difference for cell region. Two classes of lymphocyte video database provided by the cooperation hospital, Beijing You’an hospital, are used to verify the proposed approach. Experimental results show that it can quantitatively characterize lymphocyte and produce reasonably good agreement with subjective judgment by experts.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bingsong He
AU  - Xing An
AU  - Zheyi Fan
AU  - Yonggang Shi
PY  - 2013/07
DA  - 2013/07
TI  - Quantitative characterization for lymphocyte deformation in image sequences
BT  - Proceedings of the International Conference on Computer, Networks and Communication Engineering (ICCNCE 2013)
PB  - Atlantis Press
SP  - 621
EP  - 625
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccnce.2013.154
DO  - 10.2991/iccnce.2013.154
ID  - He2013/07
ER  -