The SMLM technique provides higher spatial resolution but is inherently slow due to the requirements of imaging an extremely large number of frames (>10,000 frames) of biological samples to generate a high-quality super-resolution image. Therefore, accelerating image acquisition in SMLM has been of perennial interest. Dr. Gaire previously developed a couple of fast SMLM imaging techniques (using fewer acquired frames), leveraging computational approaches such as deep learning and blind sparse inpainting to accelerate SMLM techniques. Specifically, during his Ph.D. Dr. Gaire worked on developing approaches to accelerate the following imaging techniques:

1.  Three-dimensional (3D) SMLM 

2.  Multicolor spectroscopic SMLM (sSMLM). 

For more details, see the links below in the related publications section.

Related publications:

1. Sunil Kumar Gaire, Yanhua Wang, Hao F. Zhang, Dong Liang, and Leslie Ying, "Accelerating 3D single-molecule localization microscopy using blind sparse inpainting," Journal of Biomedical Optics, 26(2), 026501, (2021).

2. Sunil Kumar Gaire, Yang Zhang, Hongyu Li, Ray Yu, Hao F. Zhang, and Leslie Ying, "Accelerating multicolor spectroscopic single-molecule localization microscopy using deep learning," Biomed. Opt. Express 11 (5), 2705-2721 (2020).

3. Sunil Kumar Gaire, Choyi Zhang, Hongyu Li, Peizhou Huang, Ruiying Liu, Haifeng Wang, Dong Liang, and Leslie Ying, "Accelerated 3D Localization Microscopy Using Blind Sparse Inpainting", IEEE ISBI 2019.

4. Dr Gaire Ph.D. dissertation: "Accelerating single-molecule localization microscopy using computational approaches"