Computational coherent Raman scattering imaging:breaking physical barriers by fusion of advanced instrumentation and data science  

作　　者：Haonan Lin Ji-Xin Cheng 

机构地区：[1]Department of Biomedical Engineering,Department of Electrical and Computer Engineering,Photonics Center,Boston University,Boston,MA 02215,USA

出　　处：《eLight》2023年第1期211-229,共19页e光学（英文）

基　　金：NIH R35GM136223;R01EB032391 to J.X.C.

摘　　要：Coherent Raman scattering(CRS)microscopy is a chemical imaging modality that provides contrast based on intrinsic biomolecular vibrations.To date,endeavors on instrumentation have advanced CRS into a powerful analytical tool for studies of cell functions and in situ clinical diagnosis.Nevertheless,the small cross-section of Raman scattering sets up a physical boundary for the design space of a CRS system,which trades off speed,signal fidelity and spectral bandwidth.The synergistic combination of instrumentation and computational approaches offers a way to break the trade-off.In this review,we first introduce coherent Raman scattering and recent instrumentation developments,then discuss current computational CRS imaging methods,including compressive micro-spectroscopy,computational volumetric imaging,as well as machine learning algorithms that improve system performance and decipher chemical information.We foresee a constant permeation of computational concepts and algorithms to push the capability boundary of CRS microscopy.

关 键 词：Coherent anti-Stokes Raman scattering Stimulated Raman scattering Computational imaging Hyperspectral imaging Deep learning 

分 类 号：O657.37[理学—分析化学]