图像分辨率
压缩传感
显微镜
帧速率
时间分辨率
分辨率(逻辑)
光学
显微镜
计算机科学
迭代重建
材料科学
合并(版本控制)
人工智能
计算机视觉
物理
情报检索
作者
Yilin He,Yunhua Yao,Dalong Qi,Yu He,Zhangcheng Huang,Pengpeng Ding,Cheng Jin,Chonglei Zhang,Lianzhong Deng,Kebin Shi,Zhenrong Sun,Xiaocong Yuan,Shian Zhang
出处
期刊:Advanced photonics
[SPIE - International Society for Optical Engineering]
日期:2023-03-10
卷期号:5 (02)
被引量:2
标识
DOI:10.1117/1.ap.5.2.026003
摘要
Various super-resolution microscopy techniques have been presented to explore fine structures of biological specimens. However, the super-resolution capability is often achieved at the expense of reducing imaging speed by either point scanning or multiframe computation. The contradiction between spatial resolution and imaging speed seriously hampers the observation of high-speed dynamics of fine structures. To overcome this contradiction, here we propose and demonstrate a temporal compressive super-resolution microscopy (TCSRM) technique. This technique is to merge an enhanced temporal compressive microscopy and a deep-learning-based super-resolution image reconstruction, where the enhanced temporal compressive microscopy is utilized to improve the imaging speed, and the deep-learning-based super-resolution image reconstruction is used to realize the resolution enhancement. The high-speed super-resolution imaging ability of TCSRM with a frame rate of 1200 frames per second (fps) and spatial resolution of 100 nm is experimentally demonstrated by capturing the flowing fluorescent beads in microfluidic chip. Given the outstanding imaging performance with high-speed super-resolution, TCSRM provides a desired tool for the studies of high-speed dynamical behaviors in fine structures, especially in the biomedical field.
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