Computer Science ›› 2016, Vol. 43 ›› Issue (5): 298-303.doi: 10.11896/j.issn.1002-137X.2016.05.057

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State Detection of Cancer Cell in Phase-contrast Microscopy Images

ZHANG Jian-hua, ZOU Yi-jie, GAO Qiang and CHEN Sheng-yong   

  • Online:2018-12-01 Published:2018-12-01

Abstract: This work described a new method based on morphology for detecting different states in a cell circle in time-lapse microscopy image of live cancer cells.A three-step approach was used as follows.First,we applied an improved level-set function to segment cancer cell images so as to identify the outline of each candidate.Then,an overall gray threshold of all the cancer cell regions was obtained through OTSU.We used this threshold to divide every cancer cell regions into two parts——dark and bright.At last,5 efficient features based on gray level,shapes and inside structures were proposed to distinguish cancer cells from interphase,mitotic prophase,mitotic metaphase and mitotic anaphase.Experiments upon T24 bladder cancer in time-lapse microscopy image were conducted,showing the proposed detection method performs well.Through this method,the position and state of cells can be detected correctly,and it has strong robustness of detecting states of cells in consecutive images.

Key words: Phase-contrast microscopy images,Cancer cell,State detection,Mitosis

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