arxiv.org/abs/1710.04957#
arxiv.org/abs/1710.04957#
33x33 mosaic with 10s SMLM acquisition/tile (3h total) - astonishing result. High throughput nanoscopy! #SMLMS2017
33x33 mosaic with 10s SMLM acquisition/tile (3h total) - astonishing result. High throughput nanoscopy! #SMLMS2017
Neural network training takes ~6 full SMLM datasets (25,000 images) - training lasts 2 to 24h. then use only 250 frames
#SMLMS2017
Neural network training takes ~6 full SMLM datasets (25,000 images) - training lasts 2 to 24h. then use only 250 frames
#SMLMS2017
#SMLMS2017
#SMLMS2017
#SMLMS2017
#SMLMS2017
Precise, robust and fast 3D localization for arbitrary point spread functions
#SMLMS2017
Precise, robust and fast 3D localization for arbitrary point spread functions
#SMLMS2017
Point defects in semi-conductors are a source of fluorescence (@ManuelTHERY not the case for microtubules I think!)
#SMLMS2017
Point defects in semi-conductors are a source of fluorescence (@ManuelTHERY not the case for microtubules I think!)
#SMLMS2017
When you look at defects in cristalline material with EM, you actually introduce defects with the e- beam
#SMLMS2017
When you look at defects in cristalline material with EM, you actually introduce defects with the e- beam
#SMLMS2017
#SMLMS2017
#SMLMS2017
#SMLMS2017
#SMLMS2017