We (Andrew York, Jan Becker, Craig Russell and I) are still working on the manuscript describing our automatic parameter-free deconvolution approach, but we've made a Google Colab notebook where you can try it out without needing to install anything: beryl.mrc-lmb.cam.ac.uk/rlgc_notebook/

Standard #deconvolution relies on a-priori assumptions about sample structure that often produce artifacts. #TRUESHARP image boosting is better. It incorporates measured information from the image to reliably remove noise and background & enhance resolution without falsification.

Beware of applying computer-vision metrics to microscopy image of biological samples. At best, you fool only yourself. Dr Siân Culley #I2K2024 #BioImageAnalysis

Introducing spIsoNet, a software tool that addresses the challenges of map anisotropy and particle misalignment in cryo-EM caused by the preferred orientation problem. The Zhou Lab Yuntao Liu CryoEM-Fan nature.com/articles/s4159…

PetaKit is great; it deals efficiently with large data, and it is easy to use. I can highly recommend it if you need deskewing, rotation and/or deconvolution for your post-processing. The repository is also not large, so it does not take much to clone it and try it out.

New scattering compensation method is compatible with widefield #Fluorescence #Microscopy, requiring tens of frames of raw data acquired using random illumination patterns, but without the need for a spatial light modulator or target sparsity: bit.ly/4i9ivOW

This is - unintentionally - an absolutely damning critique of modern biology.

Maybe the most amazing microscope paper of the year just dropped: Live 4pi-SIM (a.k.a I5S*): nature.com/articles/s4159… Having worked with Mats Gustafsson, I can attest that this is both extremely hard, but also extremely cool! Kudos to the authors! *cell.com/AJHG/fulltext/…

Microscopy Nodes: versatile 3D microscopy visualization with Blender Oane Gros, Chandni Bhickta, Granita Lokaj, Yannick Schwab, Simone Köhler and Niccolò Banterle biorxiv.org/content/early/…

MIT's "Street Fighting Mathematics" This course teaches the art of guessing results and solving problems without doing a proof or an exact calculation. Book: ocw.mit.edu/courses/18-098…

The Laplacian pyramid is the ancestor of the wavelet transform. Defines a compact multiscale representation by iterative lowpass/highpass filterings. en.wikipedia.org/wiki/Pyramid_(…

Introducing Interactive Cell Biology, a complete course solution—no textbook needed. In partnership with Macmillan Learning, delivered through Achieve. Check it out today! Visit: macmillanlearning.com/college/us/pre… to learn more. #cell #biology #education #animation

My first postdoc project! Combining neural networks & physics for self-supervised localization was a wild ride. Grateful for the journey and the team!

Optical nanoscopy, but without the OFF...! Published in Nature Physics by T.A. Hensel, J.O. Wirth, O.L. Schwarz & S.W. Hell. Check it out with open access at nature.com/articles/s4156… MPI for Multidisciplinary Sciences Max Planck Institute for Medical Research #Imaging #Optics #Waves #Microscopy

If you're at #AAAI2025, try to catch Cornell PhD student Yingheng Wang, who just presented a poster on Diffusion Variational Inference. The main idea is to use a diffusion model as a flexible variational posterior in variational inference (e.g., as the q(z|x) in a VAE) [1/3]

...and gradient descent is Bayesian inference: jmlr.org/papers/v24/22-…

This is perfectly compatible with LUNAR, which leverages temporal context up to 9 frames to achieve ultra-high localization precision. Imagine the possibilities of large-DOF in situ multicolor 3D reconstructions!

Really excited to share this Perspective from John Danial covering how technology is moving the field of fluorescence microscopy toward structural biology. nature.com/articles/s4159…

We’re excited to share LiteLoc — a lightweight and scalable deep learning framework for high-throughput single-molecule localization microscopy, enabling analysis speed of >500 MB/s on 8× RTX 4090 GPUs without compromising accuracy. rdcu.be/eztp6

Happy to share our latest work, 4Pi-SIMFLUX, which combines structured illumination with interferometric detection to achieve near-isotropic 3D localization precision of 2–3 nm and resolve sub-10 nm structural features in cells. nature.com/articles/s4159… rdcu.be/eQVxt