SACDj
Fater super-resolution fluctuation imaging: SACD reconstruction with FIJI/ImageJ.
v1.1.3
This repository is for Simplified SACD (w/o Sparse deconvolution) and will be in continued development. It is a part of publication. For details, please refer to: [Weisong Zhao et al. Enhanced detection of fluorescence fluctuation for high-throughput super-resolution imaging, Nature Photonics (2023)](https://doi.org/10.1038/s41566-023-01234-9). Please cite SACD in your publications, if it helps your research.
[Portal](https://github.com/WeisongZhao/SACDj/raw/main/SACDj_-1.1.3.jar) to the plugin.
The related MATLAB version can be found at [HERE](https://github.com/WeisongZhao/SACDm/)
You can also find some fancy results and comparisons on my [website](https://weisongzhao.github.io/home/portfolio-4-col.html#SACD).
If you are interested in our work, I wrote a [#behind_the_paper](https://engineeringcommunity.nature.com/posts/super-resolution-made-easier) post for further reading.
## SACD reconstruction
## SACD demo
These two demos can be found at the [release v1.1.3](https://github.com/WeisongZhao/SACDj/releases/tag/v1.1.3).
## Instruction
- Tips: Regarding the SACD SR frame visualization, it can be scaled with a gamma correction according to the bSOFI setting.
```python
In FIJI/ImageJ:
Process->Math->gamma(0.5)
Process->Filters->Gaussian Blur(1)
Process->Enhance Contrast(0%; normalize)
Macro:
run("Gamma...", "value=0.50");
run("Gaussian Blur...", "sigma=1");
run("Enhance Contrast...", "saturated=0 normalize");
```
- Tips: If data contains strong background, a pre background subtraction will help.
```python
In FIJI/ImageJ:
Process->Subtract background
```
## Declaration
This repository contains the java source code (Maven) for
SACD imagej plugin. This plugin is for the
Simplified SACD (w/o Sparse deconvolution), and is also accompanied with conventional
SOFI reconstruction ;
RL deconvolution; and
PSF calculation features. The development of this imagej plugin is work in progress, so expect rough edges.
If you want to reproduce the results of SACD publication, the [SACDm](https://github.com/WeisongZhao/SACDm) (Matlab version) is recommended. Due to the distance between the Fourier interpolation, deconvolution of
SACDj, and
SACDm, there may exist a gap between the results of
SACDm and
SACDj. For me, the implementations of
SACDm are more flexible and accurate.
## Version
- v1.1.3 Fixed for memory recycle & 20 times execution acceleration
- v1.1.0 Useful tools separated: RL deconvolution, PSF calculation, SOFI reconstruction & Fourier interpolation
- v1.0.0 Simplified SACD
- v0.6.0 Accelerated RL-TV deconvolution
- v0.5.0 Accelerated RL deconvolution
- v0.4.0 Born-Wolf PSF
- v0.3.0 SACD core
- v0.2.0 Fourier interpolation
- v0.1.0 Cumulant reconstruction core
## Related links:
- MATLAB version of SACD: [SACDm](https://github.com/WeisongZhao/SACDm)
- **Some fancy results and comparisons:** [my website](https://weisongzhao.github.io/home/portfolio-4-col.html#SACD)
- **Preprint:** [Weisong Zhao et al. Enhancing detectable fluorescence fluctuation for high-throughput and four-dimensional live-cell super-resolution imaging, bioRxiv (2022).](https://doi.org/10.1101/2022.12.12.520072)
- **Reference:** [Weisong Zhao et al. Enhanced detection of fluorescence fluctuation for high-throughput super-resolution imaging, Nature Photonics (2023)](https://doi.org/10.1038/s41566-023-01234-9)
Plans
- Improve the perfomance of Fourier interpolation;
- Remove redundant code and reconsitution ugly code. (in progress)
- ~~Accelarated RL deconvolution.~~
- ~~Accelarated RL-TV deconvolution.~~
- Add sparse deconvolution.
- Automation
## Open source [SACDj](https://github.com/WeisongZhao/SACDj)
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.