Journal of KIISE (정보과학회 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Automated Cell Counting Method for HeLa Cells Image based on Cell Membrane Extraction and Back-tracking Algorithm

세포막 추출과 역추적 알고리즘 기반의 HeLa 세포 이미지 자동 셀 카운팅 기법

  • 경민영 (한밭대학교 컴퓨터공학) ;
  • 박정호 (한밭대학교 생명현상융합연구센터) ;
  • 김명구 (한밭대학교 생명현상융합연구센터) ;
  • 신상모 (한밭대학교 생명현상융합연구센터) ;
  • 이현빈 (한밭대학교 컴퓨터공학)
  • Received : 2015.06.29
  • Accepted : 2015.07.30
  • Published : 2015.10.15
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Abstract

Cell counting is extensively used to analyze cell growth in biomedical research, and as a result automated cell counting methods have been developed to provide a more convenient and means to analyze cell growth. However, there are still many challenges to improving the accuracy of the cell counting for cells that proliferate abnormally, divide rapidly, and cluster easily, such as cancer cells. In this paper, we present an automated cell counting method for HeLa cells, which are used as reference for cancer research. We recognize and classify the morphological conditions of the cells by using a cell segmentation algorithm based on cell membrane extraction, and we then apply a cell back-tracking algorithm to improve the cell counting accuracy in cell clusters that have indistinct cell boundary lines. The experimental results indicate that our proposed segmentation method can identify each of the cells more accurately when compared to existing methods and, consequently, can improve the cell counting accuracy.

셀 카운팅은 세포의 성장을 분석하는 방법으로써 생물학연구에서 가장 많이 사용된다. 최근까지도 다양한 자동 셀 카운팅 기법이 제안되고 있지만 암세포와 같이 분열 속도가 빠르고 군집하려는 성질을 갖는 세포들은 분리 및 검출이 쉽지 않아 세포 이미지 분석을 통하여 셀 카운팅의 신뢰도를 높이기가 어렵다. 본 논문에서는 암 연구의 연구재료로 매우 보편적으로 사용되는 HeLa 세포 이미지 분석을 이용한 자동 셀 카운팅 방법을 제시한다. 세포막 추출 기반의 세포 분할 알고리즘을 통하여 세포의 형태적 상황을 구분하고, 세포 간 경계가 희미한 세포군집 내의 세포 분할을 위하여 역추적 알고리즘을 사용함으로써 셀 카운팅 정확도를 높인다. 실험을 통하여 제안하는 세포 분할 알고리즘이 기존의 세포 분할 알고리즘에 비해 정확함을 입증하였고, 결과적으로 매우 높은 자동 셀 카운팅 정확도를 얻을 수 있음을 확인하였다.

Keywords

Acknowledgement

Supported by : 중소기업청

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