High-speed image reconstruction enables real-time super-resolution imaging

Comparison diagram of the reconstruction process between the JSFR-SIM algorithm and the traditional Wiener-SIM algorithm.

The JSFR-SIM displays microtubule and mitochondria dynamics in real time.

Prototype of high-speed real-time super-resolution structure illumination obvious micro-imaging path (a) and rapid real-time super-resolution structure illumination obvious micro-imaging system (b). Image source: Author of the paper

Super-resolution fluorescence microscopy technology breaks the shackles of optical diffraction limits, enabling human beings to explore the nanoscale microscopic biological world in a non-destructive way, providing an unprecedented means for human beings to explore the mysteries of life. Among them, super-resolution structured light illumination microscopy (SR-SIM) has faster imaging speed, lower phototoxicity and weaker photobleaching, which is favored in the long-term dynamic observation of living cells.

“However, when performing live-cell imaging, background fluorescence not only causes a sharp drop in contrast in SR-SIM images, but also creates a large number of periodic computational artifacts, creating a huge challenge for resolving fine structures in living cells.” At the same time, the complex and time-consuming reconstruction algorithm of traditional SR-SIM makes it difficult to achieve real-time super-resolution observations. Professor Lei Ming of the School of Physics of Xi’an Jiaotong University introduced.

To do this, typically, SR-SIM users must first search for the field of interest using wide-field mode, then switch to SR-SIM mode to acquire the original structured light illumination microscope (SIM) image, then import the SIM raw image into the image post-processing process, wait for the program to complete the image reconstruction, and finally observe the super-resolution image of the sample. This cumbersome workflow is undoubtedly inefficient for microscope operators and inevitably hinders the widespread use of SR-SIM in biology laboratories.

Recently, Lei Ming’s team from the School of Physics of Xi’an Jiaotong University proposed a space-frequency domain hybrid reconstruction algorithm (JSFR-SIM), which greatly improved the image reconstruction speed of SR-SIM and solved the problem that it is difficult for traditional reconstruction methods to achieve real-time reconstruction. At the same time, the algorithm can also effectively inhibit the background fluorescence and periodic calculation artifacts during live-cell imaging, which provides great convenience for analyzing the fine structure observation of organelles in living cells. Its results were published in Advanced Photonics, No. 2, 2022.

According to reports, at present, the technology has been authorized and is applying for a number of national invention patents, and the system engineering prototype has also been developed.

After testing, this method shortens the image reconstruction time of SR-SIM to the millisecond level, and realizes the real-time display of super-resolution images, which is nearly 2 orders of magnitude faster than the Widely used Wiener-SIM algorithm. Both theoretical simulations and experimental observations have proved that the method does not lose any image quality while increasing the reconstruction speed. In addition, the authors combined the algorithm with their self-developed super-resolution structured light illumination microscope to make real-time observations of living COS-7 cells, and captured the dynamic assembly and disintegration process of microtubules and the rapid process of mitochondria tubes.

The relevant researchers believe that this method provides a rapid reconstruction means for real-time observation of the dynamic processes of organelles and biological macromolecules in living cells, greatly simplifying the workflow of SR-SIM microscope users and improving imaging efficiency, which is expected to promote the wide application of SR-SIM in biomedical laboratories. (Source: China Science Daily Zhang Xingyong)

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