BMC MethodsBioinformaticsPeer-reviewed journal article
PSSR2: a user-friendly Python package for democratizing deep learning-based point-scanning super-resolution microscopy
- Citations
- 5
Abstract
PSSR2 improves and expands on the previously established PSSR (Point-Scanning Super-Resolution) workflow for simultaneous super-resolution and denoising of undersampled microscopy data. PSSR2 is designed to put state-of-the-art technology into the hands of the general microscopy and biology research community, enabling user-friendly implementation of PSSR workflows with little to no programming experience required, especially through its integrated CLI and Napari plugin.
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Deep Learning-Based Point-Scanning Super-Resolution Imaging
Linjing Fang, Fred Monroe, … Uri Manor·Nature MethodsPeer-reviewed·Mar 8, 2021
- Self-inspired learning to denoise for live-cell super-resolution microscopy
- Zero-shot learning enables instant denoising and super-resolution in optical fluorescence microscopy
- Self-supervised denoising for structured illumination microscopy enables long-term super-resolution live-cell imaging
- Deep learning achieves super-resolution in fluorescence microscopy
H. Wang, Y. Rivenson, … A. Ozcan·bioRxiv·Apr 27, 2018
- 3D super-resolution imaging using a generalized and scalable progressive refinement method on sparse recovery (PRIS)
Xiyu Yi, Rafael Piestun, Shimon Weiss·Single Molecule Spectroscopy and Superresolution ImagingPeer-reviewed·Feb 22, 2019