This repository is for SACD reconstruction, and it will be in continued development. It is distributed as accompanying software for publication: Weisong Zhao et al. Enhanced detection of fluorescence fluctuation for high-throughput super-resolution imaging, Nature Photonics (2023). Please cite SACD in your publications, if it helps your research.

The related FIJI/ImageJ plug-in version can be found at HERE

You can also find some fancy results and comparisons on my website.

If you are interested in our work, I wrote a #behind_the_paper post for further reading.

• The SACD reconstruction requires resolution-related parameter to execute deconvolution, you can give it with objective-NA; wavelength (nm); and pixel-size (nm), or just provide resolution and pixel-size, or feed it with your own-PSF. Here are 3 examples:

SRimg = SACDm(imgstack, 'pixel', 65, 'NA', 1.3, 'wavelength', 561);
SRimg = SACDm(imgstack, 'pixel', 65, 'resolution', 250);
SRimg = SACDm(imgstack, 'psf', ownpsf);

• Please try help to get the API.

addpath(genpath('SACDm')); 
help SACDm

• Regarding the SACD SR frame visualization, it can be scaled with a gamma correction according to the bSOFI setting.

background = 0.02; order = 2;
SRimg2vis = real(SRimg.^0.5);
SRimg2vis(SRimg2vis < order * background * max(SRimg2vis(:))) = 0;
figure(2);imshow(SRimg2vis, [], 'colormap', hot)

Two demos can also be found at the SACDj release v1.1.3.

This repository contains the MATLAB source code for SACD .

If you are not a MATLAB user, you can have a try on the imagej version of SACD: SACDj.

• v0.2.0 Sparse-SACD reconstruction core
• v0.1.0 SACD reconstruction core

• ImageJ plug-in version of SACD: SACDj
• Some fancy results and comparisons: my website
• Preprint: Weisong Zhao et al. Enhancing detectable fluorescence fluctuation for high-throughput and four-dimensional live-cell super-resolution imaging, bioRxiv (2022).
• Reference: Weisong Zhao et al. Enhanced detection of fluorescence fluctuation for high-throughput super-resolution imaging, Nature Photonics (2023)

This software and corresponding methods can only be used for non-commercial use, and they are under Open Data Commons Open Database License v1.0.