Abstract

We present a camera embedded data processing method for localization microscopy (LM) with faster detectors such as scientific complementary metal-oxide semiconductor (sCMOS) cameras. Based on the natural sparsity of single molecule images, this method utilizes the field programmable gate array chip inside a camera to identify and export only the regions containing active molecules instead of raw data. Through numerical simulation and experimental analysis, we found that this method can greatly reduce data volume ($<10\%$) with negligible loss of useful information ($<0.2\%$) at molecular densities $<0.2\text{molecules}/{\mathrm{\mu m}}^2$, thus significantly reducing the challenges of data transfer, storage, and analysis in LM.

© 2013 Optical Society of America

Localization-based super-resolution microscopy with an sCMOS camera Part II: Experimental methodology for comparing sCMOS with EMCCD cameras

Fan Long, Shaoqun Zeng, and Zhen-Li Huang
Opt. Express 20(16) 17741-17759 (2012)

Localization-based super-resolution microscopy with an sCMOS camera

Zhen-Li Huang, Hongyu Zhu, Fan Long, Hongqiang Ma, Lingsong Qin, Yongfeng Liu, Jiuping Ding, Zhihong Zhang, Qingming Luo, and Shaoqun Zeng
Opt. Express 19(20) 19156-19168 (2011)

Evaluation of sCMOS cameras for detection and localization of single Cy5 molecules

Saumya Saurabh, Suvrajit Maji, and Marcel P. Bruchez
Opt. Express 20(7) 7338-7349 (2012)

Accelerating multi-emitter localization in super-resolution localization microscopy with FPGA-GPU cooperative computation

Dan Gui, Yunjiu Chen, Weibing Kuang, Mingtao Shang, Zhengxia Wang, and Zhen-Li Huang
Opt. Express 29(22) 35247-35260 (2021)

Algorithmic corrections for localization microscopy with sCMOS cameras - characterisation of a computationally efficient localization approach

Ruisheng Lin, Alexander H. Clowsley, Isuru D. Jayasinghe, David Baddeley, and Christian Soeller
Opt. Express 25(10) 11701-11716 (2017)