Segmentation of clustered cells in negative phase contrast images with integrated light intensity and cell shape information

Segmentation of clustered cells in negative phase contrast images with integrated light intensity and cell shape information
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利用集成光强度和细胞形状信息对负相差图像中的簇状细胞进行分割

DOI:
10.1111/jmi.12673
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发表时间:
2018-05
影响因子:
2
通讯作者:
Zaicheng Zhang
Zaicheng Zhang
中科院分区:
工程技术4区
文献类型:
--
作者:
Yuliang Wang;Chunqi Wang;Zaicheng Zhang

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Automated cell segmentation plays a key role in characterisations of cell behaviours for both biology research and clinical practices. Currently, the segmentation of clustered cells still remains as a challenge and is the main reason for false segmentation. In this study, the emphasis was put on the segmentation of clustered cells in negative phase contrast images. A new method was proposed to combine both light intensity and cell shape information through the construction of grey‐weighted distance transform (GWDT) within preliminarily segmented areas. With the constructed GWDT, the clustered cells can be detected and then separated with a modified region skeleton‐based method. Moreover, a contour expansion operation was applied to get optimised detection of cell boundaries. In this paper, the working principle and detailed procedure of the proposed method are described, followed by the evaluation of the method on clustered cell segmentation. Results show that the proposed method achieves an improved performance in clustered cell segmentation compared with other methods, with 85.8% and 97.16% accuracy rate for clustered cells and all cells, respectively.
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