Accurate Cell Segmentation Based on Biological Morphology Features

Jianfeng Cao; Zhongying Zhao; Hong Yan

doi:10.1109/SMC.2018.00572

Accurate Cell Segmentation Based on Biological Morphology Features

Jianfeng Cao, Zhongying Zhao, Hong Yan

Department of Biology

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

3 Citations (Scopus)

Abstract

Microscopic imaging has many applications in biological experiments. It is important to determine the cell locations in an image before other analysis tasks take place. In this paper, we propose a novel method to obtain cell and membrane segmentation based on the combination of k nearest neighbor clustering and biological morphology constraints. First, we produce preliminary segmentation with the watershed transformation. Then the segmentation results are optimized based on the morphological characteristics of the membrane. This method provides us with well-segmented cells and membranes, which significantly reduces errors in cell image analysis.

Original language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
Publisher	IEEE
Pages	3380-3383
Number of pages	4
ISBN (Electronic)	9781538666500
DOIs	https://doi.org/10.1109/SMC.2018.00572
Publication status	Published - 2 Jul 2018
Event	2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 - Miyazaki, Japan Duration: 7 Oct 2018 → 10 Oct 2018

Publication series

Name	Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

Conference

Conference	2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
Country/Territory	Japan
City	Miyazaki
Period	7/10/18 → 10/10/18

Scopus Subject Areas

Information Systems
Information Systems and Management
Health Informatics
Artificial Intelligence
Computer Networks and Communications
Human-Computer Interaction

User-Defined Keywords

biological constraints
cell and membrane segmentation
nearest neighbor clustering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/SMC.2018.00572

Cite this

Cao, J., Zhao, Z., & Yan, H. (2018). Accurate Cell Segmentation Based on Biological Morphology Features. In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 (pp. 3380-3383). Article 8616569 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018). IEEE. https://doi.org/10.1109/SMC.2018.00572

@inproceedings{b85a651191da4bfb85ccf2c566b65e4d,

title = "Accurate Cell Segmentation Based on Biological Morphology Features",

abstract = "Microscopic imaging has many applications in biological experiments. It is important to determine the cell locations in an image before other analysis tasks take place. In this paper, we propose a novel method to obtain cell and membrane segmentation based on the combination of k nearest neighbor clustering and biological morphology constraints. First, we produce preliminary segmentation with the watershed transformation. Then the segmentation results are optimized based on the morphological characteristics of the membrane. This method provides us with well-segmented cells and membranes, which significantly reduces errors in cell image analysis.",

keywords = "biological constraints, cell and membrane segmentation, nearest neighbor clustering",

author = "Jianfeng Cao and Zhongying Zhao and Hong Yan",

note = "Funding Information: This work is supported by the Hong Kong Research Grants Council (Project C1007-15G).; 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 ; Conference date: 07-10-2018 Through 10-10-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/SMC.2018.00572",

language = "English",

series = "Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018",

publisher = "IEEE",

pages = "3380--3383",

booktitle = "Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018",

address = "United States",

}

Cao, J, Zhao, Z & Yan, H 2018, Accurate Cell Segmentation Based on Biological Morphology Features. in Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018., 8616569, Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, IEEE, pp. 3380-3383, 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, Miyazaki, Japan, 7/10/18. https://doi.org/10.1109/SMC.2018.00572

Accurate Cell Segmentation Based on Biological Morphology Features. / Cao, Jianfeng; Zhao, Zhongying; Yan, Hong.
Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. IEEE, 2018. p. 3380-3383 8616569 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Accurate Cell Segmentation Based on Biological Morphology Features

AU - Cao, Jianfeng

AU - Zhao, Zhongying

AU - Yan, Hong

N1 - Funding Information: This work is supported by the Hong Kong Research Grants Council (Project C1007-15G).

PY - 2018/7/2

Y1 - 2018/7/2

N2 - Microscopic imaging has many applications in biological experiments. It is important to determine the cell locations in an image before other analysis tasks take place. In this paper, we propose a novel method to obtain cell and membrane segmentation based on the combination of k nearest neighbor clustering and biological morphology constraints. First, we produce preliminary segmentation with the watershed transformation. Then the segmentation results are optimized based on the morphological characteristics of the membrane. This method provides us with well-segmented cells and membranes, which significantly reduces errors in cell image analysis.

AB - Microscopic imaging has many applications in biological experiments. It is important to determine the cell locations in an image before other analysis tasks take place. In this paper, we propose a novel method to obtain cell and membrane segmentation based on the combination of k nearest neighbor clustering and biological morphology constraints. First, we produce preliminary segmentation with the watershed transformation. Then the segmentation results are optimized based on the morphological characteristics of the membrane. This method provides us with well-segmented cells and membranes, which significantly reduces errors in cell image analysis.

KW - biological constraints

KW - cell and membrane segmentation

KW - nearest neighbor clustering

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U2 - 10.1109/SMC.2018.00572

DO - 10.1109/SMC.2018.00572

M3 - Conference proceeding

AN - SCOPUS:85062220030

T3 - Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

SP - 3380

EP - 3383

BT - Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

PB - IEEE

T2 - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

Y2 - 7 October 2018 through 10 October 2018

ER -

Accurate Cell Segmentation Based on Biological Morphology Features

Abstract

Publication series

Conference

Scopus Subject Areas

User-Defined Keywords

UN SDGs

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