RT Journal Article
SR Electronic
T1 Deep Learning-Based Point-Scanning Super-Resolution Imaging
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 740548
DO 10.1101/740548
A1 Linjing Fang
A1 Fred Monroe
A1 Sammy Weiser Novak
A1 Lyndsey Kirk
A1 Cara R. Schiavon
A1 Seungyoon B. Yu
A1 Tong Zhang
A1 Melissa Wu
A1 Kyle Kastner
A1 Yoshiyuki Kubota
A1 Zhao Zhang
A1 Gulcin Pekkurnaz
A1 John Mendenhall
A1 Kristen Harris
A1 Jeremy Howard
A1 Uri Manor
YR 2019
UL http://biorxiv.org/content/early/2019/09/07/740548.abstract
AB Point scanning imaging systems (e.g. scanning electron or laser scanning confocal microscopes) are perhaps the most widely used tools for high resolution cellular and tissue imaging. Like all other imaging modalities, the resolution, speed, sample preservation, and signal-to-noise ratio (SNR) of point scanning systems are difficult to optimize simultaneously. In particular, point scanning systems are uniquely constrained by an inverse relationship between imaging speed and pixel resolution. Here we show these limitations can be mitigated via the use of deep learning-based super-sampling of undersampled images acquired on a point-scanning system, which we termed point-scanning super-resolution (PSSR) imaging. Oversampled, high SNR ground truth images acquired on scanning electron or Airyscan laser scanning confocal microscopes were ‘crappified’ to generate semi-synthetic training data for PSSR models that were then used to restore real-world undersampled images. Remarkably, our EM PSSR model could restore undersampled images acquired with different optics, detectors, samples, or sample preparation methods in other labs. PSSR enabled previously unattainable 2 nm resolution images with our serial block face scanning electron microscope system. For fluorescence, we show that undersampled confocal images combined with a multiframe PSSR model trained on Airyscan timelapses facilitates Airyscan-equivalent spatial resolution and SNR with ∼100x lower laser dose and 16x higher frame rates than corresponding high-resolution acquisitions. In conclusion, PSSR facilitates point-scanning image acquisition with otherwise unattainable resolution, speed, and sensitivity.