Ultrafast cell edge detection by line‐scan time‐stretch microscopy. Issue 1 (27th July 2018)

• Record Type: Journal Article
• Authors: Dai, Bo; He, Lu; Zheng, Lulu; Fu, Yongfeng; Wang, Kaimin; Sui, Guodong; Zhang, Dawei; Zhuang, Songlin; Wang, Xu
• Is Part Of: Journal of biophotonics. Volume 12:Issue 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-07-27
• Subjects: cell analysis -- edge detection -- pattern recognition -- ultrafast imaging; Photonics -- Periodicals; Optical materials -- Periodicals; Optics -- Periodicals; Medical instruments and apparatus -- Periodicals; 621.3605
• DOI: 10.1002/jbio.201800044
• Languages: English
• ISSNs: 1864-063X

Abstract

Abstract : Ultrafast time‐stretch imaging technique recently attracts an increasing interest for applications in cell classification due to high throughput and high sensitivity. A novel imaging modality of time‐stretch imaging technique for edge detection is proposed. Edge detection based on the directional derivative is realized using differential detection. As the image processing is mainly implemented in the physical layer, the computation complexity of edge extraction is significantly reduced. An imaging system for edge detection with the scan rate of 77.76 MHz is experimentally demonstrated. Resolution target is first measured to verify the feasibility of the edge extraction. Furthermore, various cells, including red blood cells, lung cancer cells and breast cancer cells, are detected. The edges of cancerous cells present in a completely different form. The imaging system for edge detection would be a good candidate for high‐throughput cell classification. Abstract : An ultrafast time‐stretch imaging technique for edge detection is demonstrated at the scan rate of 77.76 MHz for extracting the edges of various cells including red blood cells, lung cancer cells and breast cancer cells. As the edge detection is implemented in the physical layer, the computation complexity in the back‐end digital signal processing could be significantly reduced. The cells can be easily and rapidly identified by distinguishing the edges.