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Hey #STED, #MINFLUX people,
To continue the public discussion, I list here some of the points I made during my talk.
Summary: MINFLUX is a promising technology but at an early stage of development esp for biological research.
Thread👇
cc @Stefan_W_Hell @BalzarottiFran
To continue the public discussion, I list here some of the points I made during my talk.
Summary: MINFLUX is a promising technology but at an early stage of development esp for biological research.
Thread👇
cc @Stefan_W_Hell @BalzarottiFran
Disclaimer 1: I haven't seen or worked with #MINFLUX setup, my arguments mainly on application-side
Disclaimer 2: I asked these questions via email (Sept 2020) and requested raw data and codes but haven't received a reply yet
I hope @rita_strack @naturemethods can help!
Disclaimer 2: I asked these questions via email (Sept 2020) and requested raw data and codes but haven't received a reply yet
I hope @rita_strack @naturemethods can help!
You can learn more about #MINFLUX from this excellent talk by @Stefan_W_Hell
Also, some papers making an effort in this direction
Also, some papers making an effort in this direction
Excited to introduce #3DRCAN for denoising, super resolution and expansion microscopy. Super proud of this colab with Hari Shroff, Jiji Chen et al.
@NIBIBgov @arpcomplex
Preprint: biorxiv.org/content/10.110…
Code: github.com/AiviaCommunity…
#microscopy #aimicroscopy #aivia
1/17
@NIBIBgov @arpcomplex
Preprint: biorxiv.org/content/10.110…
Code: github.com/AiviaCommunity…
#microscopy #aimicroscopy #aivia
1/17
"Three-dimensional residual channel attention networks denoise and sharpen fluorescence microscopy image volumes"
J Chen, H Sasaki, H Lai, Y Su, J Liu, Y Wu, A Zhovmer, C Combs, I Rey-Suarez, H Chang, C Huang, X Li, M Guo, S Nizambad, A Upadhyaya, J Lee, L Lucas, H Shroff.
2/17
J Chen, H Sasaki, H Lai, Y Su, J Liu, Y Wu, A Zhovmer, C Combs, I Rey-Suarez, H Chang, C Huang, X Li, M Guo, S Nizambad, A Upadhyaya, J Lee, L Lucas, H Shroff.
2/17
We are particularly interested in characterizing the limits of #deeplearning based approaches to image restoration. You will find several experiments comparing several best-in-class approaches: #3DRCAN, #CARE, #SRResNet and #ESRGAN.
#microscopy #aimicroscopy #iSIM
3/17
#microscopy #aimicroscopy #iSIM
3/17
