Evidence map›Paper›PMID 39246531›Full record

ArticleJournal of biomedical optics2024

Statistical estimation theory detection limits for label-free imaging.

Lang Wang, Maxine Varughese, Ali Pezeshki, Randy Bartels

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lang WangMorgridge Institute for Research, Madison, Wisconsin, United States.ORCID 0000-0001-6820-5449
Maxine VarugheseMorgridge Institute for Research, Madison, Wisconsin, United States.ORCID 0009-0009-5551-3552
Ali PezeshkiColorado State University, Fort Collins, Colorado, United States.
Randy BartelsMorgridge Institute for Research, Madison, Wisconsin, United States.ORCID 0000-0003-0530-0435

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 Cramér-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.

Indexed as

Spectrum Analysis, RamanAlgorithmsHumansImage Processing, Computer-AssistedMicroscopyModels, Statisticalcoherent Ramanlabel-free microscopynonlinear microscopyphotothermalquantitative phasetransient absorption

Identifiers

PMID39246531
PMCPMC11379408

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.