Abstract
Induced pluripotent stem cells (iPSCs) have huge potential in regenerative medicine research and industrial applications. However, building automatic method without using cell staining technique for iPSCs identification is an important challenge. To improve the efficiency of producing iPSCs, we build an accurate and noninvasive iPSCs colonies detection method via ensemble Yolo network based on the self-collected bright-field microscopy images. Meanwhile, test-time augmentation (TTA) is leveraged to further improve the detection result of our iPSCs colonies detection method. Extensive experimental results on our dataset demonstrate that our method obtains quite favorable detection performance with the highest F1 score of 0.867 and the highest mean average precision score of 0.898, which outperforms most mainstream methods.
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