Statistical estimation theory detection limits for label-free imaging

被引:0
|
作者
Wang, Lang [1 ]
Varughese, Maxine [1 ,2 ]
Pezeshki, Ali [2 ]
Bartels, Randy [1 ]
机构
[1] Morgridge Inst Res, Madison, WI 53715 USA
[2] Colorado State Univ, Ft Collins, CO USA
基金
美国国家科学基金会;
关键词
label-free microscopy; nonlinear microscopy; coherent Raman; quantitative phase; photothermal; transient absorption; HARMONIC-GENERATION MICROSCOPY; RAMAN-SPECTROSCOPY; PHASE MICROSCOPY; LIVING CELLS; ABSORPTION; NANOPARTICLES; PRINCIPLES; 2-COLOR; TISSUE; TOOL;
D O I
10.1117/1.JBO.29.S2.S22716
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Significance The emergence of label-free microscopy techniques has significantly improved our ability to precisely characterize biochemical targets, enabling non-invasive visualization of cellular organelles and tissue organization. However, understanding each label-free method with respect to the specific benefits, drawbacks, and varied sensitivities under measurement conditions across different types of specimens remains a challenge. Aim We link all of these disparate label-free optical interactions together and compare the detection sensitivity within the framework of statistical estimation theory. Approach To achieve this goal, we introduce a comprehensive unified framework for evaluating the bounds for signal detection with label-free microscopy methods, including second-harmonic generation, third-harmonic generation, coherent anti-Stokes Raman scattering, coherent Stokes Raman scattering, stimulated Raman loss, stimulated Raman gain, stimulated emission, impulsive stimulated Raman scattering, transient absorption, and photothermal effect. A general model for signal generation induced by optical scattering is developed. Results Based on this model, the information obtained is quantitatively analyzed using Fisher information, and the fundamental constraints on estimation precision are evaluated through the Cram & eacute;r-Rao lower bound, offering guidance for optimal experimental design and interpretation. Conclusions We provide valuable insights for researchers seeking to leverage label-free techniques for non-invasive imaging applications for biomedical research and clinical practice.
引用
收藏
页数:24
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