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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.

 

Dual-mode visible/near-infrared imaging systems, including a bioinspired six-channel design and more conventional four-channel implementations, have transitioned from a niche in surveillance to general use in machine vision. However, the demosaicing routines that transform the raw images from these sensors into processed images that can be consumed by humans or computers rely on assumptions that may not be appropriate when the two portions of the spectrum contribute different information about a scene. A solution can be found in a family of demosaicing routines that utilize interpolating polynomials and splines of different dimensionalities and orders to process images with minimal assumptions.

 

Tumor-targeted fluorescent probes in the near-infrared spectrum can provide invaluable information about the location and extent of primary and metastatic tumors during intraoperative procedures to ensure no residual tumors are left in the patient's body. Even though the first fluorescence-guided surgery was performed more than 50 years ago, it is still not accepted as a standard of care in part due to the lack of efficient and non-toxic targeted probes approved by regulatory agencies around the world. Herein, we report protease-activated cationic gelatin nanoparticles encapsulating indocyanine green (ICG) for the detection of primary breast tumors in murine models with high tumor-to-background ratios. Upon intravenous administration, these nanoprobes remain optically silent due to the energy resonance transfer among the bound ICG molecules. As the nanoprobes extravasate and are exposed to the acidic tumor microenvironment, their positive surface charges increase, facilitating cellular uptake. The internalized nanoprobes are activated upon proteolytic degradation of gelatin to allow high contrast between the tumor and normal tissue. Since both gelatin and ICG are FDA-approved for intravenous administration, this activatable nanoprobe can lead to quick clinical adoption and improve the treatment of patients undergoing image-guided cancer surgery. 

Recent advancements in nanofabrication technology has led to commercialization of single-chip polarization and color-polarization imaging sensors in the visible spectrum. Novel applications have arisen with the emergence of these sensors leading to questions about noise in the reconstructed polarization images. In this paper, we provide theoretical analysis for the input and output referred noise for the angle and degree of linear polarization information. We validated our theoretical model with experimental data collected from a division of focal plane polarization sensor. Our data indicates that the noise in the angle of polarization images depends on both incident light intensity and degree of linear polarization and is independent of the incident angle of polarization. However, noise in degree of linear polarization images depends on all three parameters: incident light intensity, angle and degree of linear polarization. This theoretical model can help guide the development of imaging setups to record optimal polarization information.

 

We examine the impact of illumination, aperture, and sample thickness on two division-of-focal-plane (DoFP) polarimeters, one created using a standard 3 T pixel and the other with a forward-biased, logarithmic pixel. Across all measured metrics the logarithmic DoFP polarimeter was better able to track real-time changes in collagen alignment than the standard DoFP polarimeter.