Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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Microscopic Image-based Cancer Cell Viability-related Phenotype Extraction

현미경 영상 기반 암세포 생존력 관련 표현형 추출

  • Misun Kang (Department of Computer Software Engineering, Soonchunhyang University)
  • 강미선 (순천향대학교 컴퓨터소프트웨어공학과)
  • Received : 2023.05.02
  • Accepted : 2023.05.18
  • Published : 2023.06.30
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Abstract

During cancer treatment, the patient's response to drugs appears differently at the cellular level. In this paper, an image-based cell phenotypic feature quantification and key feature selection method are presented to predict the response of patient-derived cancer cells to a specific drug. In order to analyze the viability characteristics of cancer cells, high-definition microscope images in which cell nuclei are fluorescently stained are used, and individual-level cell analysis is performed. To this end, first, image stitching is performed for analysis of the same environment in units of the well plates, and uneven brightness due to the effects of illumination is adjusted based on the histogram. In order to automatically segment only the cell nucleus region, which is the region of interest, from the improved image, a superpixel-based segmentation technique is applied using the fluorescence expression level and morphological information. After extracting 242 types of features from the image through the segmented cell region information, only the features related to cell viability are selected through the ReliefF algorithm. The proposed method can be applied to cell image-based phenotypic screening to determine a patient's response to a drug.

Keywords

Acknowledgement

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구입니다(No. RS-2022-00165681). 본 연구에서 사용된 암세포 현미경 영상 데이터는 삼성서울병원 연구센터로부터 제공받아서 수행되었으며 이에 감사드립니다.

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