Acta Optica Sinica, Volume. 41, Issue 15, 1511001(2021)
Deep Learning-Based Detection Method for Mitosis in Living Cells
Owing to the spatiotemporal randomness of mitosis, the automatic identification and accurate location of mitosis in living cells are challenging tasks for researchers. Herein, a deep learning-based detection method was proposed to automatically identify and locate mitosis in living cells. Here, we built a deep neural network called DetectNet by improving the backbone network of YOLOv3 and introducing an attention mechanism. Under the condition of bright-field microscopic imaging, multiscale images of living cells were acquired and then a dataset was constructed to train the network. The trained network DetectNet was compared with multiple object detection algorithms, and its effectiveness was verified. Experimental results show that aiming at the bright-field microscopic images, DetectNet can directly identify and locate mitosis from the multiscale live cell images with a large field, achieving a higher detection accuracy and faster detection speed compared with other multiple object detection algorithms. Thus, DetectNet shows a great potential application value in the fields of biology and medicine.
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Baosheng Ke, Ying Li, Zhenbo Ren, Jianglei Di, Jianlin Zhao. Deep Learning-Based Detection Method for Mitosis in Living Cells[J]. Acta Optica Sinica, 2021, 41(15): 1511001
Category: Imaging Systems
Received: Dec. 9, 2020
Accepted: Mar. 5, 2021
Published Online: Aug. 11, 2021
The Author Email: Di Jianglei (jiangleidi@nwpu.edu.cn), Zhao Jianlin (jlzhao@nwpu.edu.cn)