Quantitative evaluation of intensity fidelity of superresolution reconstruction for structured illumination microscopy  

作　　者：Yujun Tang Linbo Wang Gang Wen Hui Li 

机构地区：[1]School of Biomedical Engineering(Suzhou)Division of Life Sciences and Medicine University of Science and Technology of China Suzhou 230041,P.R.China [2]Jiangsu Key Laboratory of Medical Optics Suzhou Institute of Biomedical Engineering and Technology Chinese Academy of Sciences,Suzhou 215163,P.R.China [3]Laboratory of Advanced Theranostic Materials and Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences,Ningbo 315201 P.R.China

出　　处：《Journal of Innovative Optical Health Sciences》2025年第1期153-163,共11页创新光学健康科学杂志(英文)

基　　金：supported by the National Natural Science Foundation of China[Grant Nos.62205367 and 62141506];Suzhou Basic Research Pilot Project[Grant Nos.SSD2023006 and SJC2021013];Jiangsu Provincial Key Research and Development Program[Grant No.BE2020664].

摘　　要：Super-resolution structured illumination microscopy(SR-SIM)relies heavily on post-processing reconstruction to obtain high-quality SR images from raw data.Although many SIM reconstruction algorithms have been developed to recover fine cellular structures with high fidelity even from the noisy data,whether the pixel intensities of reconstructed SR images are still proportional to the original fluorescence intensity has been less explored.The linearity between the intensity before and after reconstruction is de fined as the intensity fidelity.Here,we proposed a method to evaluate the reconstructed SR image intensity fidelity at different spatial frequencies.With the proposed metric,we systematically investigated the impact of the key factors on the intensity fidelity in the standard Wiener-SIM reconstructions with simulated data,then evaluated the intensity fidelity of the SR images reconstructed by representative open-source packages.Our work provides a reference for SR-SIM image intensity fidelity improvement.

关 键 词：Structured illumination microscopy super-resolution image reconstruction intensity fidelity spectrum optimization 

分 类 号：R318[医药卫生—生物医学工程] TP391.41[医药卫生—基础医学]