[1P4-J-10] Vision, speech: organisms and medicine

[1P4-J-10-03] Cell Image Segmentation by Integrating Generative Adversarial Network for Each Class

〇Hiroki Tsuda¹, Kazuhiro Hotta¹ (1. Meijo University)

Keywords: Segmentation, Cell image, Deep learning

Human experts segment cell images manually now, and the criterion for segmentation varies on each expert. As a result, subjective results are obtained. If we develop an automatic segmentation method, we can obtain objective results by the same criteria. This paper proposes a cell image segmentation method using Generative Adversarial Network (GAN) with multiple different roles. The proposed method improved the segmentation accuracy in comparison to conventional pix2pix.