Digital-SMLM for precisely localizing emitters within the diffraction limit.
Ontology highlight
ABSTRACT: Precisely pinpointing the positions of emitters within the diffraction limit is crucial for quantitative analysis or molecular mechanism investigation in biomedical research but has remained challenging unless exploiting single molecule localization microscopy (SMLM). Via integrating experimental spot dataset with deep learning, we develop a new approach, Digital-SMLM, to accurately predict emitter numbers and positions for sub-diffraction-limit spots with an accuracy of up to 98 % and a root mean square error as low as 14 nm. Digital-SMLM can accurately resolve two emitters at a close distance, e.g. 30 nm. Digital-SMLM outperforms Deep-STORM in predicting emitter numbers and positions for sub-diffraction-limited spots and recovering the ground truth distribution of molecules of interest.
SUBMITTER: Jia Z
PROVIDER: S-EPMC11465993 | biostudies-literature | 2024 Aug
REPOSITORIES: biostudies-literature
ACCESS DATA