Instant Image Denoising Plugin for ImageJ using Convolutional Neural Networks
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Abstract (arXiv)
We present a new convolutional neural network (CNN) based ImageJ plugin for fluorescence microscopy image denoising with an average improvement of 7.5 dB in peak signal-to-noise ratio (PSNR) and denoising instantly within 80 msec.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Jun 2020.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 0; 2024: 1.
4 papers.
- 2021Deep learning-based super-resolution fluorescence microscopy on small datasetscited by 1
- 2021Convolutional Neural Network Denoising in Fluorescence Lifetime Imaging Microscopy (FLIM)cited by 0
- 2022Low dosage 3D volume fluorescence microscopy imaging using compressive sensingcited by 0
- 2024Deep-Learning Recognition of Scanning Transmission Electron Microscopy: Quantifying and Mitigating the Influence of Gaussian Noisescited by 0
- 2024Deep-Learning Recognition of Scanning Transmission Electron Microscopy: Quantifying and Mitigating the Influence of Gaussian Noises25 Sep 2024
- 2022Low dosage 3D volume fluorescence microscopy imaging using compressive sensing3 Jan 2022
- 2021Convolutional Neural Network Denoising in Fluorescence Lifetime Imaging Microscopy (FLIM)7 Mar 2021
- 2021Deep learning-based super-resolution fluorescence microscopy on small datasets7 Mar 2021