Digital-SMLM for precisely localizing emitters within the diffraction limit
Author:
Jia Zhe1, Zhou Lingxiao1, Li Haoyu1, Ni Jielei1, Chen Danni1, Guo Dongfei1, Cao Bo1, Liu Gang1, Liang Guotao1, Zhou Qianwen1, Yuan Xiaocong1ORCID, Ni Yanxiang1ORCID
Affiliation:
1. Nanophotonics Research Center, Institute of Microscale Optoelectronics & State Key Laboratory of Radio Frequency Heterogeneous Integration, College of Physics and Optoelectronic Engineering & Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province , 47890 Shenzhen University , Shenzhen 518060 , China
Abstract
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. We have validated the generalization capability of Digital-SMLM using independent experimental data. Furthermore, Digital-SMLM complements SMLM by providing more accurate event number and precise emitter positions, enabling SMLM to closely approximate the natural state of high-density cellular structures.
Funder
National Natural Science Foundation of China Shenzhen Science and Technology Planning Project Stable Support Project of Shenzhen the Scientific Instrument Developing Project of ShenZhen University Shenzhen Peacock Plan
Publisher
Walter de Gruyter GmbH
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