Structured illumination microscopy, or SIM, has become a primary technique for imaging live cells given its full-field imaging and low photodamage. This method, however, requires at least nine raw images for image reconstruction and the processing time needed is computationally expensive and time-consuming.

Qian et al. developed a significantly improved reconstruction method for SIM images that requires fewer images and less time compared with traditional techniques.

“We propose a frame-reduced SIM reconstruction algorithm with accelerated correlation-enabled parameter estimation,” said author Chao Zuo. “Compared with traditional SIM technology, the proposed algorithm achieves high-quality super-resolution reconstruction in complex experimental environments with fewer raw images and faster processing speed.”

The method works by first applying a modulation-assigned spatial filter to remove background noise and then employing a coarse-to-fine accelerated correlation algorithm. This algorithm helps reduce the number of frames needed by using a phase-shifting strategy and pixel-wise fluorescence pre-calibration.

The authors experimentally showed that the new method improves the computation efficiency of image processing by a factor of 4.5 while simultaneously creating high-quality and high-resolution images even with just two raw frames.

The new method helps improve imaging speed and efficiency. With shorter imaging time, this method will also allow for lower phototoxicity and photobleaching of cells, which will enable longer live cell observations.

“This will facilitate new biological discoveries and bring new possibilities for solving problems in cell biology, cancer research, developmental biology, and neuroscience,” said author Jiaming Qian.

Source: “Robust frame-reduced structured illumination microscopy with accelerated correlation-enabled parameter estimation,” by Jiaming Qian, Yu Cao, Kailong Xu, Ying Bi, Weiyi Xia, Qian Chen, and Chao Zuo, Applied Physics Letters (2022). The article can be accessed at

This paper is part of the Advances in Optical Microscopy for Bioimaging Collection. Learn more here.