Influence of signal-to-noise ratio on DoLP and AoP measurements during reflectance-mode division-of-focal plane Stokes polarimetry of biological tissues.
Leanne E IannucciViktor GruevSpencer P LakePublished in: Biomedical optics express (2024)
Stokes polarimeter based endoscopes are emerging as an area of technology where polarization imaging can greatly impact clinical care by improving diagnostic tools without the use of exogenous contrast. Image acquisition in minimally invasive surgical settings is often beset by inherently limited illumination. A comprehensive analysis of how signal-to-noise (SNR) propagates through Stokes polarimetric outcomes such as degree of linear polarization (DoLP) and angle of polarization (AoP) in low light is important for future interpretation of data acquired in low-light conditions. A previously developed theoretical model of quantitative polarized light imaging (QPLI) analysis described SNR as a function of both incident light intensity and DoLP. When polarized light interacts with biological tissues, the resultant DoLP of exiting light is dependent on the underlying tissue microstructure. Therefore, in this study we explore how low light impacts SNR of QPLI outcomes of DoLP and AoP differently in tissue phantoms of varying microstructures. Data are compared to theoretical solutions of SNR of DoLP and AoP. Tissues were additionally loaded to varying magnitudes of strain to investigate how variable SNR affects the ability to discern dynamic realignment in biological tissues. We observed a high degree of congruency between experimental and theoretical data, with SNR depending on both light intensity and DoLP. Additionally, we found that AoP may have a greater resilience to noise overall than DoLP and, as such, may be particularly useful in conditions where light is inherently limited.
Keyphrases
- high resolution
- gene expression
- minimally invasive
- magnetic resonance
- healthcare
- cardiovascular disease
- electronic health record
- air pollution
- drug delivery
- computed tomography
- type diabetes
- deep learning
- metabolic syndrome
- photodynamic therapy
- skeletal muscle
- insulin resistance
- pain management
- fluorescent probe
- data analysis
- white matter
- contrast enhanced
- mass spectrometry
- glycemic control