Improvement of cell image analysis system based on CNN

Yuma Hotta; Toshiyuki Yoshida; Takuya Kajitani; Masaya Oki

doi:10.1117/12.2625980

30 April 2022 Improvement of cell image analysis system based on CNN

Yuma Hotta, Toshiyuki Yoshida, Takuya Kajitani, Masaya Oki

Proceedings Volume 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022; 121771U (2022) https://doi.org/10.1117/12.2625980
Event: International Workshop on Advanced Imaging Technology 2022 (IWAIT 2022), 2022, Hong Kong, China

Abstract

The authors have proposed a cell image analysis system that offers the mechanisms of cell segmentation, tracking, and fluorescence analysis, where the segmentation step is the crucial one that dominates the overall performance. This paper proposes a CNN-based segmentation technique for cell images to improve the segmentation accuracy in the analysis system. In the segmentation step, the division timing of cells is important together with a geometrical accuracy of segmented cells. The proposed technique makes use of two sets of fluorescent (FL) cell images as well as common bright-field (BF) images to boost the accuracy of the division timing. These image sets are fed into an extended version of a multi-input U-Net to generate accurate cell markers utilized as seeds in the watershed postprocessing. The experimental results demonstrate that the proposed technique gives a satisfactory accuracy in terms both of the geometrical shape and division timing in the cell segmentation task.

Citation Download Citation

Yuma Hotta, Toshiyuki Yoshida, Takuya Kajitani, and Masaya Oki "Improvement of cell image analysis system based on CNN", Proc. SPIE 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022, 121771U (30 April 2022); https://doi.org/10.1117/12.2625980

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