Year: 2024
Type: article
Abstract: Super-resolution structured illumination microscopy (SR-SIM) is one of the important techniques that are most suitable for live-cell imaging. The reconstructed SR-SIM images are noisy once the raw images are recorded with low-light exposure. Here, we propose a new network (entitled the ND-SIM network) to denoise the SR images reconstructed using frequency-domain algorithms (FDAs). We demonstrate that ND-SIM can yield artifact-free SR images using raw images with an average photon count down to 20 per pixel while achieving comparable resolution to the ground truth (GT) obtained with high-light exposure. We can envisage that the ND-SIM will be widely applied for the long-term, super-resolution live-cell imaging of various bioprocesses in the future.
Source: Photonics
Institution: Xidian University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,728
Awards: G1434766483, G1483925613, G1908353606, G2408142620, G2429333155, G2641296755, G3079538671, G342071462, G3584298751, G3762927813, G3929276222, G4137291945, G4517206687, G458170782, G4936067112, G525442035, G5569935634, G5674421737, G632834847, G6612464864, G6834887245, G6867695250, G7278971744, G7319951050, G773702619, G7976622628, G8381467882, G8490802960, G8751217351, G8780090566
OpenAlex ID: W4401869688