寿,使SparseFLIM

Binglin Shen1, Yuan Lu2, Fangyin Guo1

  • 1Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, China.

Communications biology
|October 21, 2024
PubMed
概括

SparseFLIM使用深度学习来从更少的光子中重建高质量的光终身成像显微镜 (FLIM). 这种智能方法可以显著加快FLIM获取速度,而不会牺牲图像保真度.

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