Optical coherence tomography (OCT) has been applied to investigate heart development because of its capability to image both structure and function of tiny beating embryonic hearts. Labeling heart structures is necessary for quantifying mechanical functions such as cardiac motion, wall strain, blood flow and shear stress, of looping hearts. Since manual segmentation is time-consuming and labor- intensive, this study aimed to use deep learning to automatically extract dynamic shapes including the myocardium, the endocardial cushions, and the lumen of beating embryonic hearts from 4-D OCT images. This will benefit research on heart development, especially studies requiring large cohorts of embryos.

We investigated the correlation of the blood optical attenuation coefficient (OAC) and the blood glucose concentration (BGC). The blood OAC was measured in mouse retina in vivo through OCT angiography (OCTA). The arteries and veins presented a blood OAC change of ~0.05-0.07 mm-1 per 10 mg/dl and a significant elevation of blood OAC in diabetic mice was observed. Besides, the veins had a higher correlation coefficient between the measured blood OAC and BGC than that of the arteries. The blood OAC-BGC correlation suggests a concept of non-invasive OCTA-based glucometry, allowing a fast assessment of the blood glucose of specific vessels.

A biofilm morphology transition is a dynamic process that mediates growth and dispersion. The development of the dynamic process shows the enhancement of the power-law tail that is observed while the biofilms grown at the air-agar interface are submerged in a medium. Environmentally driven morphology transitions of biofilm were analyzed by acquiring the phase displacements of the Doppler shift and linearly decomposed by ballistic (Cauchy) and diffusive (Gaussian) distributions. The analysis provides the internal dynamic characteristics of biofilm that pave the way between the conventional dynamic parameters and the anomalous diffusion parameters.

The simulation of statistically accurate time-integrated dynamic speckle patterns using a physics-based model that accounts for spatially varying sample properties is yet to be presented in biomedical optics. In this work, we propose a solution to this important problem based on the Karhunen-Loève expansion of the electric field, and apply our method to the formalisms of both laser speckle contrast imaging and diffuse correlation spectroscopy. We validate our technique against solutions for speckle contrast for different forms of homogeneous field, and also show that our method can readily be extended to cases with spatially varying sample properties.

A variety of diffuse optical methods use laser speckle contrast and its statistics to non-invasively determine blood flow. In most cases, this implies very low detected count-rates which leads to systematic errors in determining the correct speckle statistics. We have developed a comprehensive method for simulating realistic speckle contrast resultant from light propagation in tissue taking into account experimental and fundamental sources of noise. Results of the simulation are used to determine the relationship of these parameters on the precision and accuracy of the speckle contrast signal.

We present the design of an innovative instrument for time-gated diffuse correlation spectroscopy. It features a 1064nm pulsed sub-ns long coherence-length laser operating up to 75MHz, a 100-channel in-FPGA correlator and a novel time-gated 32×32 InP/InGaAs-based Single Photon Avalanche Diode (SPAD) array with sub-nanosecond gating capabilities operating up to 10MHz repetition rate. We present components experimental characterization and preliminary validations on a liquid phantom. This testing is informing us for a revision of the photodetector which will allow to reach up to 192 optical channels towards functional blood flow changes measurements with full head coverage.

We have previously demonstrated a novel Fourier domain diffuse correlation spectroscopy instrument that makes use of holographic camera-based detection, and which is capable of making in vivo pulsatile flow measurements. In this work, we detail considerations to further characterise the signal-to-noise ratio performance of our system. These include demonstration and elimination of laser multimode behaviour, and correction for the camera's modulation transfer function to ensure faithful reconstruction of measured intensity profiles. We document the effect of varying laser source power, and also demonstrate a technique to remove spatiotemporally correlated noise sources to reveal the performance limit of our instrument.

Time-domain diffuse correlation spectroscopy (TD-DCS) is a non-invasive optical technique, which measures tissue blood flow with path-length resolution. Ideally, this technique requires a pulsed laser with an adequate illumination power, a long coherence length, and a narrow instrument response function (IRF), while available laser modules cannot satisfy all these conditions. We systematically characterized three pulsed laser sources and compared their performances using phantom and in vivo measurements. We found that each laser has the potential to be used in TD-DCS applications. Also, the effects caused by the IRF are more significant than the effect of the limited coherence length.

We developed and applied parallel interferometric near-infrared spectroscopy (πNIRS) to noninvasively monitor pulsatile blood flow deep into the human tissue in vivo. With the unique capability of accessing complex information (amplitude and phase) about the sample with more than 1000 parallel channels, we can sense blood flow with only 20 ms integration time, making the πNIRS one of the fastest and comprehensive diffuse optical method.

The autocorrelation-based optical coherence tomography motility metric (OCT M) is sensitive to intracellular motion and independent of shot noise. M is widely applied to quantify drug and toxicant responses in 3D tissue models. To improve data scanning and storage efficiency, we propose a temporally uneven compressed sensing method to estimate short- and long-time correlations from OCT data. First, simulated OCT signals assuming diffusive motion demonstrates the method and its limitations. Then, M values derived from OCT data in mammary epithelial cell spheroids exposed to estrogen demonstrate that compressed M accurately reconstructs uncompressed M values at up to 8x compression ratio.

In pulse oximetry, arterial oxygen saturation (SpO2) is calculated from near-infrared spectroscopy (NIRS) data using the modified Beer-Lambert Law. Tissue homogeneity is assumed, and the photon mean pathlength (〈L〉) needs to be known or calibrated for. We aim to develop a transabdominal fetal pulse oximeter, where SpO2 = 40-70% and the homogeneity assumption and experimental calibration cannot be applied. Our approach relies on spectral fitting of normalized 〈L〉 from NIRS measurements with analytical description of 〈L〉. Data from simulations and human subjects are presented. Our preliminary results show that the self-calibrated algorithm can accurately extract SpO2 changes in homogenous tissue.

Ovulation is essential for mammalian reproduction. The aim of this study was to investigate how ovulated eggs are transported within the ovarian bursa to the infundibulum. We utilized optical coherence tomography (OCT) for dynamic imaging of ovulatory processes in mice. The OCT imaging enabled spatio-temporal analysis of the eggs in the ovarian bursa, and indicated that the periodic movement of the bursa could contribute to the egg transport. This study demonstrates intravital optical coherence tomography as a promising tool for in vivo analysis of mammalian ovulation and suggests potential mechanisms for the egg transport to the infundibulum.

Spermatozoa motility is critical for successfully reaching the egg and fertilization. One of essential transitions in sperm behavior within the female reproductive tract required for fertilization is hyperactivation. Our group established an innovative volumetric in vivo sperm tracking approach using OCT through an intravital imaging window. This study is focused on the development of new functional OCT quantitative measures for the analysis of sperm hyperactivation state. The quantitative parameters were first developed in vitro; then optimized and tested in vivo. This work established a potential quantitative approach for differentiating sperm hyperactivation status based on their trajectories in vivo.