Acta Optica Sinica, Volume. 40, Issue 17, 1710001(2020)

Cell Image Segmentation Method Based on Residual Block and Attention Mechanism

Wenxiu Zhang1,2,3、*, Zhencai Zhu1,2,3, Yonghe Zhang1,2,3, Xinyu Wang1,2, and Guopeng Ding1,2
Author Affiliations
  • 1Innovation Academy for Microsatellite, Chinese Academy of Sciences, Shanghai 201203, China
  • 2Key Laboratory of Microsatellites, Chinese Academy of Sciences, Shanghai 201203, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
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    Herein, a cell segmentation model is proposed based on the U-Net and combination of residual block and attention mechanism. This model aims at addressing the problems of uneven brightness and low contrast between a cell and background of cell images collected using a phase contrast microscope. First, the U-Net with encoder-decoder structure is used to conduct the initial segmentation on cell images. Hereafter, the residual block is introduced into the U-Net to strengthen the propagation ability of the features and extract more cell-detail information. Finally, the attention mechanism is used to increase the weight of the cell area and reduce the interference of uneven brightness and low contrast on the model. The experimental results show that compared with other models, the proposed model exhibit better segmentation results in visual effects and objective evaluation indicators.

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    Wenxiu Zhang, Zhencai Zhu, Yonghe Zhang, Xinyu Wang, Guopeng Ding. Cell Image Segmentation Method Based on Residual Block and Attention Mechanism[J]. Acta Optica Sinica, 2020, 40(17): 1710001

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    Paper Information

    Category: Image Processing

    Received: Mar. 6, 2020

    Accepted: May. 29, 2020

    Published Online: Aug. 24, 2020

    The Author Email: Zhang Wenxiu (zwxy@mail.ustc.edu.cn)

    DOI:10.3788/AOS202040.1710001

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