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Introduction：

We developed a two-stage framework using parallel modified U-Nets together with seed guided water-mesh algorithm for automatic segmentation and yeast cells counting. The proposed framework was tested with independent images, of which the ground truth of yeast cell number and locations was done by skilled technicians. Our method improved cell counting by reducing bias and demonstrated a 99.35% consistent recall rate of experienced manual counting, and decreased the time required from 5 minutes on average to only 5 seconds for each image.

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Reference

Yan Kong, Hui Li, Yongyong Ren, Georgi Z. Genchev, Xiaolei Wang, Hongyu Zhao, Zhiping Xie, and Hui Lu, "Automated yeast cells segmentation and counting using a parallel U-Net based two-stage framework," OSA Continuum 3, 982-992 (2020)