Early diagnosis of ocular diseases improves the understanding of pathophysiology and aids in accurate monitoring and effective treatment. Advanced, multimodal ocular imaging platforms play a crucial role in visualization of ocular components and provide clinicians with a valuable tool for evaluating various eye diseases. Here, for the first time we present a non-contact, multiwavelength photoacoustic remote sensing (PARS) microscopy and swept-source optical coherence tomography (SS-OCT) for in-vivo functional and structural imaging of the eye. The system provides complementary imaging contrasts of optical absorption and optical scattering, and is used for simultaneous, non-contact, in-vivo imaging of murine eye. Results of vasculature and structural imaging as well as melanin content in the retinal pigment epithelium layer are presented. Multiwavelength PARS microscopy using Stimulated Raman scattering is applied to enable in-vivo, non-contact oxygen saturation estimation in the ocular tissue. The reported work may be a major step towards clinical translation of ophthalmic technologies and has the potential to advance the diagnosis and treatment of ocular diseases.
Abstract-This paper addresses human decision-making in supervisory control of a team of unmanned vehicles performing search missions. Previous work has proposed the use of a twoalternative choice framework, in which operators declare the presence or absence of a target in an image. It has been suggested that relooking at a target at some later time can help operators improve the accuracy of their decisions but it is not well understood how -or how well -operators handle this relook task with multiple UAVs. This paper makes two novel contributions in developing a choice model for a search task with relooks. First, we extend a previously proposed queueing model of the human operator by developing a retrial queue model that formally includes relooks. Since real models may deviate from some of the theoretical assumptions made in the requeueing literature, we develop a Discrete Event Simulation (DES) that embeds operator models derived from previous experimental data and present new results in the predicted performance of multi-UAV visual search tasks with relook. Our simulation results suggest that while relooks can in fact improve detection accuracy and decrease mean search times per target, the overall fraction found correctly is extremely sensitive to increased relooks.
Stimulated Raman scattering (SRS) has been widely used in functional photoacoustic microscopy to generate multiwavelength light and target multiple chromophores inside tissues. Despite offering a simple, cost-effective technique with a high pulse repetition rate; it suffers from pulse-to-pulse intensity fluctuations and power drift that can affect image quality. Here, we propose a new technique to improve the temporal stability of the pulsed SRS multiwavelength source. We achieve this by lowering the temperature of the SRS medium. The results suggest that a decrease in temperature causes an improvement of temporal stability of the output, considerable rise in the intensity of the SRS peaks, and significant increase of SRS cross section. The application of the method is shown for in vivo functional imaging of capillary networks in a chicken embryo chorioallantois membrane using photoacoustic remote sensing microscopy.
Photoacoustic remote sensing (PARS) microscopy is an emerging label-free optical absorption imaging modality. PARS operates by capturing nanosecond-scale optical fluctuations produced by photoacoustic pressures. These time-domain (TD) variations are usually projected by amplitude to determine optical absorption magnitude. However, valuable details on a target’s material properties (e.g., density, speed of sound) are contained within the TD signals. This work uses a novel, to the best of our knowledge, clustering method to learn TD features, based on signal shape, which relate to underlying material traits. A modified K-means method is used to cluster TD data, capturing representative signal features. These features are then used to form virtual colorizations which may highlight tissues based on their underlying material properties. Applied in fresh resected murine brain tissue, colorized visualizations highlight distinct regions of tissue. This may potentially facilitate differentiation of tissue constituents (e.g., myelinated and unmyelinated axons, cell nuclei) in a single acquisition.
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