Learning the imaging mechanism directly from optical microscopy observations

作     者：ZE-HAO WANG LONG-KUN SHAN TONG-TIAN WENG TIAN-LONG CHEN XIANG-DONG CHEN ZHANG-YANG WANG GUANG-CAN GUO FANG-WEN SUN ZE-HAO WANG;LONG-KUN SHAN;TONG-TIAN WENG;TIAN-LONG CHEN;XIANG-DONG CHEN;ZHANG-YANG WANG;GUANG-CAN GUO;FANG-WEN SUN

作者机构：CAS Key Laboratory of Quantum InformationUniversity of Science and Technology of ChinaHefei 230026China CAS Center for Excellence in Quantum Information and Quantum PhysicsUniversity of Science and Technology of ChinaHefei 230026China University of Texas at AustinAustinTexas 78705USA Hefei National LaboratoryUniversity of Science and Technology of ChinaHefei 230088China 

出 版 物：《Photonics Research》 (光子学研究（英文版）)

年 卷 期：2024年第12卷第1期

页      面：7-26页

核心收录：

学科分类：070207[理学-光学] 07[理学] 08[工学] 0803[工学-光学工程] 0702[理学-物理学] 

基　　金：Innovation Program for Quantum Science and Technology(2021ZD0303200) CAS Project for Young Scientists in Basic Research(YSBR-049) National Natural Science Foundation of China(62225506) Anhui Provincial Key Research and Development Plan(2022b13020006) USTC Center for Micro and Nanoscale Research and Fabrication 

主　　题：optical emitter mechanism 

摘      要：The optical microscopy image plays an important role in scientific research through the direct visualization of the nanoworld,where the imaging mechanism is described as the convolution of the point spread function(PSF)and *** on a priori knowledge of the PSF or equivalent PSF,it is possible to achieve more precise exploration of the ***,it is an outstanding challenge to directly extract the PSF from microscopy ***,with the help of self-supervised learning,we propose a physics-informed masked autoencoder(PiMAE)that enables a learnable estimation of the PSF and emitters directly from the raw microscopy *** demonstrate our method in synthetic data and real-world experiments with significant accuracy and noise *** outperforms DeepSTORM and the Richardson–Lucy algorithm in synthetic data tasks with an average improvement of 19.6%and 50.7%(35 tasks),respectively,as measured by the normalized root mean square error(NRMSE)*** is achieved without prior knowledge of the PSF,in contrast to the supervised approach used by DeepSTORM and the known PSF assumption in the Richardson–Lucy *** method,PiMAE,provides a feasible scheme for achieving the hidden imaging mechanism in optical microscopy and has the potential to learn hidden mechanisms in many more systems.