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.
Keyphrases
- high resolution
- high throughput
- loop mediated isothermal amplification
- label free
- single cell
- real time pcr
- induced apoptosis
- machine learning
- deep learning
- computed tomography
- cell therapy
- physical activity
- breast cancer cells
- stem cells
- red blood cell
- oxidative stress
- magnetic resonance
- single molecule
- fluorescence imaging
- endoplasmic reticulum stress