Deep-learning based denoising and reconstruction of super-resolution structured illumination microscopy images
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Tung-Cheng Wang | Mark Schüttpelz | Thomas Huser | Marcel Müller | Wolfram Schenck | Zafran Hussain Shah | Philip Maurice Scheidig | Axel Schneider | T. Huser | M. Schüttpelz | Marcel Müller | Wolfram Schenck | Tung-Cheng Wang | Axel Schneider
[1] Maria Smedh,et al. Successful optimization of reconstruction parameters in structured illumination microscopy – a practical guide , 2018 .
[2] Kyoung Mu Lee,et al. Enhanced Deep Residual Networks for Single Image Super-Resolution , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[3] Djemel Ziou,et al. Image Quality Metrics: PSNR vs. SSIM , 2010, 2010 20th International Conference on Pattern Recognition.
[4] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[5] Emilio Soria Olivas,et al. Handbook of Research on Machine Learning Applications and Trends : Algorithms , Methods , and Techniques , 2009 .
[6] Yun Fu,et al. Image Super-Resolution Using Very Deep Residual Channel Attention Networks , 2018, ECCV.
[7] Suliana Manley,et al. Quantitative evaluation of software packages for single-molecule localization microscopy , 2015, Nature Methods.
[8] Pietro Lio,et al. ML-SIM: A deep neural network for reconstruction of structured illumination microscopy images , 2020, ArXiv.
[9] T. Huser,et al. DMD-based super-resolution structured illumination microscopy visualizes live cell dynamics at high speed and low cost , 2019, bioRxiv.
[10] Bryant B. Chhun,et al. Super-Resolution Video Microscopy of Live Cells by Structured Illumination , 2009, Nature Methods.
[11] Liangyi Chen,et al. A protocol for structured illumination microscopy with minimal reconstruction artifacts , 2019, Biophysics Reports.
[12] Fenqiang Zhao,et al. Deep learning enables structured illumination microscopy with low light levels and enhanced speed , 2019, Nature Communications.
[13] O. Mandula,et al. Structured illumination microscopy of a living cell , 2009, 2011 International Quantum Electronics Conference (IQEC) and Conference on Lasers and Electro-Optics (CLEO) Pacific Rim incorporating the Australasian Conference on Optics, Lasers and Spectroscopy and the Australian Conference on Optical Fibre Technology.
[14] Tibor Novák,et al. TestSTORM: Versatile simulator software for multimodal super-resolution localization fluorescence microscopy , 2017, Scientific Reports.
[15] Jaakko Lehtinen,et al. Noise2Noise: Learning Image Restoration without Clean Data , 2018, ICML.
[16] C. Felser,et al. Negative magnetoresistance without well-defined chirality in the Weyl semimetal TaP , 2015, Nature Communications.
[17] Yu-Bin Yang,et al. Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections , 2016, NIPS.
[18] P. Xi,et al. Fast, long-term, super-resolution imaging with Hessian structured illumination microscopy , 2018, Nature Biotechnology.
[19] M. Davidson,et al. Noninvasive Imaging beyond the Diffraction Limit of 3D Dynamics in Thickly Fluorescent Specimens , 2012, Cell.
[20] M. Kunitski,et al. Double-slit photoelectron interference in strong-field ionization of the neon dimer , 2018, Nature Communications.
[21] Karel Fliegel,et al. SIMToolbox: a MATLAB toolbox for structured illumination fluorescence microscopy , 2015, Bioinform..
[22] Thomas Huser,et al. Video-rate multi-color structured illumination microscopy with simultaneous real-time reconstruction , 2019, Nature Communications.
[23] Eric Betzig,et al. Tiled Reconstruction Improves Structured Illumination Microscopy , 2020, bioRxiv.
[24] Sebastian Ruder,et al. Universal Language Model Fine-tuning for Text Classification , 2018, ACL.
[25] Xiaocong Yuan,et al. Fast structured illumination microscopy via deep learning , 2020 .
[26] Abhay Patil,et al. Learning Image Restoration without Clean Data , 2019 .
[27] M. Sauer,et al. Super-resolution microscopy demystified , 2019, Nature Cell Biology.
[28] Alessandro Foi,et al. Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering , 2007, IEEE Transactions on Image Processing.
[29] M. Gustafsson,et al. Super-resolution 3D microscopy of live whole cells using structured illumination , 2011, Nature Methods.
[30] Loic A. Royer,et al. Content-aware image restoration: pushing the limits of fluorescence microscopy , 2018, Nature Methods.
[31] F. Peyrin,et al. A residual U-Net network with image prior for 3D image denoising , 2021, 2020 28th European Signal Processing Conference (EUSIPCO).
[32] Atsushi Matsuda,et al. Strategic and practical guidelines for successful structured illumination microscopy , 2017, Nature Protocols.
[33] Reto Fiolka,et al. Phase optimisation for structured illumination microscopy. , 2013, Optics express.
[34] Gavriel Salomon,et al. T RANSFER OF LEARNING , 1992 .
[35] M. Davidson,et al. Time-lapse two-color 3D imaging of live cells with doubled resolution using structured illumination , 2012, Proceedings of the National Academy of Sciences.
[36] M. Gustafsson,et al. Three-dimensional resolution doubling in wide-field fluorescence microscopy by structured illumination. , 2008, Biophysical journal.
[37] Manuel Llinás,et al. Dissecting the role of PfAP2-G in malaria gametocytogenesis , 2020, Nature Communications.
[38] Wolfgang Hübner,et al. Open-source image reconstruction of super-resolution structured illumination microscopy data in ImageJ , 2016, Nature Communications.
[39] Peng Xi,et al. Structured Illumination Microscopy Image Reconstruction Algorithm , 2016, IEEE Journal of Selected Topics in Quantum Electronics.
[40] 拓海 杉山,et al. “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告 , 2017 .
[41] Rainer Heintzmann,et al. Super-Resolution Structured Illumination Microscopy. , 2017, Chemical reviews.
[42] M. Gustafsson. Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy , 2000, Journal of microscopy.