Advanced Photonics, Volume. 1, Issue 6, 066001(2019)
Deep-learning cell imaging through Anderson localizing optical fiber
Fig. 1. Schematic of the cell imaging setup and the architecture of the DCNN.
Fig. 2. Cell imaging of different types of cells: (a)–(c) test data for human red blood cells and (d)–(f) test data for cancerous human stomach cells. All data are collected with straight GALOF, at room temperature with 0-mm imaging depth. The length of the scale bar in (a1) is
Fig. 3. Multiple depth cell imaging: (a)–(f) Test data for human red blood cells. All data are collected with straight GALOF at room temperature. All three images in each column are from the same depth. The length of the scale bar in (a1) is
Fig. 4. Cell imaging at different temperatures. (a1)–(c1) Test raw images of human red blood cells collected at 20°C, 35°C, and 50°C, respectively. The scale bar length in (a1) is
Fig. 5. Cell imaging under bending. (a)–(e) Data in each column correspond to examples with the bending offset distance listed above. The definition of offset distance is illustrated in
Fig. 6. Cell imaging transfer learning. (a)–(c) Sample cell images in the set of training data. The scale bar length in (a) is
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Jian Zhao, Yangyang Sun, Hongbo Zhu, Zheyuan Zhu, Jose E. Antonio-Lopez, Rodrigo Amezcua Correa, Shuo Pang, Axel Schulzgen, "Deep-learning cell imaging through Anderson localizing optical fiber," Adv. Photon. 1, 066001 (2019)
Category: Research Articles
Received: Sep. 11, 2019
Accepted: Oct. 19, 2019
Published Online: Nov. 12, 2019
The Author Email: Zhao Jian (jianzhao@knights.ucf.edu)