University of Illinois Urbana-Champaign
Gradient fitting algorithm is for high-speed 3D localization of fluorescent emitters in astigmatism-based microscopy (e.g., STORM and PALM).
Programming Language: MATLAB
Publication: The algorithm of this code has been published in the following paper: Ma H, Xu J, Jin J, Gao Y, Lan L, Liu Y. Fast and precise 3D fluorophore localization based on gradient fitting. Scientific Reports, 5: 14335, 2015.
Source Code: Source code is available on our github depository.
WindSTORM is a high-speed high-density single-molecule localization algorithm based on linear deconvolution for super-resolution microscopy (e.g., STORM and PALM).
Programming Language: MATLAB
Publication: The algorithm of this code has been published in the following paper: Ma H, Xu J, Liu Y. WindSTORM: Robust online image processing for high-throughput nanoscopy. Science Advances, eaaw0683, 2019.
Source Code: The source code and testing dataset are available on our shared drive (password: Biophotonics).
EVER stands for extreme-value based emitter recovery, which is used to correct for heterogeneous background in the raw data of single moelcule localization microscopy (e.g., STORM and PALM).
Programming Language: ImageJ Plugin (Java)
Publication: The algorithm of this code has been described in detail in the following two publications:
1. Ma H, Xu J, Liu Y. WindSTORM: Robust online image processing for high-throughput nanoscopy.
Science Advances, eaaw0683, 2019.
Source Code: The source code is available on our github depository.
We optimized convolutional neural network for nuclei segmentation of single-molecule localization-based (e.g., STORM or PALM) super-resolution images. A conveninent Colab notebooks were developed, which can be executed in both google Cloud-based and local runtime. The local run-time version is suited for large dataset when uploading images is slow. We provided some sample STORM images of cell nuclei and labeled images from cultured cells and tissue in the "Examples" folder. For very large image size (e.g., 10240x10240 or 20480x20480 pixels), "Image Tile" notebook is used to split them into 5120x5120 suited for STORM-based nuclei segmentation.
Programming Language: Jupyter Notebook (Python)
Publication: The details of the method has been described in detail in the following publication:
Mela CA, Liu Y. Application of convolutional neural networks towards nuclei segmentation in localization-based super-resolution fluorescence microscopy images.
BMC Bioinformatics, 22, 325, 2021.
Source Code: The source code is available on our github depository.