Meeting experiments at the diffraction barrier: an in-silico widefield fluorescence microscopy
Mahajan, S.; Tang, T.
Show abstract
Fluorescence microscopy allows the visualization of live cells and their components, but even with advances in super- resolution microscopy, atomic resolution remains unattainable. On the other hand, molecular simulations (MS) can easily access atomic resolution, but comparison with experimental microscopy images has not been possible. In this work, a novel in-silico widefield fluorescence microscopy is proposed, which reduces the resolution of MS to generate images comparable to experiments. This technique will allow cross-validation and compound the knowledge gained from experiments and MS. We demonstrate that in-silico images can be produced with different optical axis, object focal planes, exposure time, color combinations, resolution, brightness and amount of out-of-focus fluorescence. This allows the generation of images that resemble those obtained from widefield, confocal, light-sheet, two-photon and super-resolution microscopy. This technique not only can be used as a standalone visualization tool for MS, but also lays the foundation for other in-silico microscopy methods.
Matching journals
The top 10 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Optimization of highly inclined Illumination for diffraction-limited and super-resolution microscopy 97%
- Computationally-efficient spatiotemporal correlation analysis super-resolves anomalous diffusion 96%
- Divide and Conquer: Real-time maximum likelihood fitting of multiple emitters for super-resolution localization microscopy 96%
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Full three-dimensional imaging deep through multicellular thick samples with subcellular resolution by structured illumination microscopy and adaptive optics 96%
- Fast holographic scattering compensation for deep tissue biologicalimaging 96%
- High sensitivity cameras can lower spatial resolution in high-resolution optical microscopy 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.