Accurate Cell Segmentation Based on Biological Morphology Features

Jianfeng Cao, Zhongying ZHAO, Hong Yan

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

1 Citation (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 languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3380-3383
Number of pages4
ISBN (Electronic)9781538666500
DOIs
Publication statusPublished - 16 Jan 2019
Event2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 - Miyazaki, Japan
Duration: 7 Oct 201810 Oct 2018

Publication series

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

Conference

Conference2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
Country/TerritoryJapan
CityMiyazaki
Period7/10/1810/10/18

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

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