ArticleBiomedical optics express2022
Three-dimensional opto-thermo-mechanical model for predicting photo-thermal optical coherence tomography responses in multilayer geometries.
Article in Biomedical optics express, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The trial behind it
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Who cites it
5 citing papers in PubMed.
- Phase-sensitive photothermal optical coherence tomography: decoupling optical and thermal tissue properties.Biomedical optics express · 2026Article
- Design Principles Of Inorganic-Protein Hybrid Materials for Biomedicine.Exploration (Beijing, China) · 2025Review
- Artificial neural network for enhancing signal-to-noise ratio and contrast in photothermal optical coherence tomography.Scientific reports · 2024Article
- Machine Learning-Assisted Short-Wave InfraRed (SWIR) Techniques for Biomedical Applications: Towards Personalized Medicine.Journal of personalized medicine · 2023Review
- Photothermal optical coherence tomography for 3D live cell detection and mapping.Optics continuum · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Photothermal optical coherence tomography (PT-OCT) is a functional extension of OCT with the ability to generate qualitative maps of molecular absorptions co-registered with the micron-resolution structural tomograms of OCT. Obtaining refined insight into chemical information from PT-OCT images, however, requires solid understanding of the multifactorial physics behind generation of PT-OCT signals and their dependence on system and sample parameters. Such understanding is needed to decouple the various physical effects involved in the PT-OCT signal to obtain more accurate insight into sample composition. In this work, we propose an analytical model that considers the opto-thermo-mechanical properties of multi-layered samples in 3-D space, eliminating several assumptions that have been limiting previous PT-OCT models. In parametric studies, the model results are compared with experimental signals to investigate the effect of sample and system parameters on the acquired signals. The proposed model and the presented findings open the door for: 1) better understanding of the effects of system parameters and tissue opto-thermo-mechanical properties on experimental signals; 2) informed optimization of experimentation strategies based on sample and system parameters; 3) guidance of downstream signal processing for predicting tissue molecular composition.
Identifiers
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Registered trials
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