Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userSimulating optical coherence tomography for observing nerve activity: a finite difference time domain bi-dimensional model
59
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We present a finite difference time domain (FDTD) model for computation of A line scans in time domain optical coherence tomography (OCT). By simulating only the end of the two arms of the interferometer and computing the interference signal in post processing, it is possible to reduce the computational time required by the simulations and, thus, to simulate much bigger environments. Moreover, it is possible to simulate successive A lines and thus obtaining a cross section of the sample considered. In this paper we present the model applied to two different samples: a glass rod filled with water-sucrose solution at different concentrations and a peripheral nerve. This work demonstrates the feasibility of using OCT for non-invasive, direct optical monitoring of peripheral nerve activity, which is a long-sought goal of neuroscience.
rate research
Read More
Optical coherence tomography (OCT) is a widely used imaging technique in the micrometer regime, which gained accelerating interest in medical imaging %and material testing in the last twenty years. In up-to-date OCT literature [5,6] certain simplifying assumptions are made for the reconstructions, but for many applications a more realistic description of the OCT imaging process is of interest. In mathematical models, for example, the incident angle of light onto the sample is usually neglected or %although having a huge impact on the laser power inside the sample is usually neglected or a plane wave description for the light-sample interaction in OCT is used, which ignores almost completely the occurring effects within an OCT measurement process. In this article, we make a first step to a quantitative model by considering the measured intensity as a combination of back-scattered Gaussian beams affected by the system. In contrast to the standard plane wave simplification, the presented model includes system relevant parameters such as the position of the focus and the spot size of the incident laser beam, which allow a precise prediction of the OCT data and therefore ultimately serves as a forward model. The accuracy of the proposed model - after calibration of all necessary system parameters - is illustrated by simulations and validated by a comparison with experimental data obtained from a 1300nm swept-source OCT system.
We report on a technically simple approach to achieve high-resolution and high-sensitivity Fourier-domain OCT imaging in the mid-infrared range. The proposed OCT system employs an InF3 supercontinuum source. A specially designed dispersive scanning spectrometer based on a single InAsSb point detector is employed for detection. The spectrometer enables structural OCT imaging in the spectral range from 3140 nm to 4190 nm with a characteristic sensitivity of over 80 dB and an axial resolution below 8 um. The capabilities of the system are demonstrated for imaging of porous ceramic samples and transition-stage green parts fabricated using an emerging method of lithography-based ceramic manufacturing. Additionally, we demonstrate the performance and flexibility of the system by OCT imaging using an inexpensive low-power (average power of 16 mW above 3 um wavelength) mid-IR supercontinuum source.
Optical coherence tomography angiography (OCTA) has been established as a powerful tool for investigating vascular diseases and is expected to become a standard of care technology. However, its widespread clinical usage is hindered by technical gaps such as limited field of view (FOV), lack of quantitative flow information, and suboptimal motion correction. Here we report a new imaging platform, termed spectrally extended line field (SELF) OCTA that provides advanced solutions to the above-mentioned challenges. SELF-OCTA breaks the speed limitations and achieves two-fold gain in FOV without sacrificing signal strength through parallel image acquisition. Towards quantitative angiography, the frequency flow imaging mechanism overcomes the imaging speed bottleneck by obviating the requirement for superfluous B-scans. In addition, the frequency flow imaging mechanism facilitates OCTA-data based motion tracking with overlap between adjacent line fields. Since it can be implemented in any existing OCT device without significant hardware modification or affecting existing functions, we expect that SELF-OCTA will make non-invasive, wide field, quantitative, and low-cost angiographic imaging available to larger patient populations.
We apply three optical coherence tomography (OCT) image analysis techniques to extract morphometric information from OCT images obtained on peripheral nerves of rat. The accuracy of each technique is evaluated against histological measurements accurate to +/-1 um. The three OCT techniques are: 1) average depth resolved profile (ADRP); 2) autoregressive spectral estimation (AR-SE); and, 3) correlation of the derivative spectral estimation (CoD-SE). We introduce a scanning window to the ADRP technique which provides transverse resolution, and improves epineurium thickness estimates - with the number of analysed images showing agreement with histology increasing from 2/10 to 5/10 (Kruskal-Wallis test, {alpha} = 0.05). A new method of estimating epineurium thickness, using the AR-SE technique, showed agreement with histology in 6/10 analysed images (Kruskal-Wallis test, {alpha} = 0.05). Using a tissue sample in which histology identified two fascicles with an estimated difference in mean fibre diameter of 4 um, the AR-SE and CoD-SE techniques both correctly identified the fascicle with larger fibre diameter distribution but incorrectly estimated the magnitude of this difference as 0.5um. The ability of OCT signal analysis techniques to extract accurate morphometric details from peripheral nerve is promising but restricted in depth by scattering in adipose and neural tissues.
The speckle statistics of optical coherence tomography images of biological tissue have been studied using several historical probability density functions. A recent hypothesis implies that underlying power-law distributions in the medium structure, such as the fractal branching vasculature, will contribute to power-law probability distributions of speckle statistics. Specifically, these are the Burr type XII distribution for speckle amplitude, the Lomax distribution for intensity, and the generalized logistic distribution for log amplitude. In this study, these three distributions are fitted to histogram data from nine optical coherence tomography scans of various biological tissues and samples. The distributions are also compared with conventional distributions such as the Rayleigh, K, and gamma distributions. The results indicate that these newer distributions based on power laws are, in general, more appropriate models and support the plausibility of their use for characterizing biological tissue. Potentially, the governing power-law parameter of these distributions could be used as a biomarker for tissue disease or pathology.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
