ABSTRACT
A swept source (SS)-based circular-state (CS) polarization-sensitive optical coherence tomography (PS-OCT) constructed entirely with polarization-maintaining fiber optics components is proposed with the experimental verification. By means of the proposed calibration scheme, bulk quarter-wave plates can be replaced by fiber optics polarization controllers to, therefore, realize an all-fiber optics CS SSPS-OCT. We also present a numerical dispersion compensation method, which can not only enhance the axial resolution, but also improve the signal-to-noise ratio of the images. We demonstrate that this compact and portable CS SSPS-OCT system with an accuracy comparable to bulk optics systems requires less stringent lens alignment and can possibly serve as a technology to realize PS-OCT instrument for clinical applications (e.g., endoscopy). The largest deviations in the phase retardation (PR) and fast-axis (FA) angle due to sample probe in the linear scanning and a rotation angle smaller than 65 deg were of the same order as those in stationary probe setups. The influence of fiber bending on the measured PR and FA is also investigated. The largest deviations of the PR were 3.5 deg and the measured FA change by ~12 to 21 deg. Finally, in vivo imaging of the human fingertip and nail was successfully demonstrated with a linear scanning probe.
Subject(s)
Fiber Optic Technology , Tomography, Optical Coherence/methods , Calibration , Endoscopy/methods , Equipment Design , Fingers/pathology , Fourier Analysis , Humans , Image Processing, Computer-Assisted/methods , Nails/pathology , Optics and Photonics , Reproducibility of Results , Signal Processing, Computer-Assisted , Signal-To-Noise RatioABSTRACT
We report a semiautomatic algorithm that is specialized for rapid analysis of beat-to-beat contraction-relaxation parameters of the heart in Drosophila. The presented algorithm adapts the general graph theoretical image segmentation algorithm and a histogram-based thresholding algorithm, which can measure many cardiac parameters, including heart rate, heart period, diastolic and systolic intervals, and end-diastolic and end-systolic areas. Additionally, dynamic cardiac functions, such as arrhythmia index and percent fractional shortening, can be automatically calculated for all the recorded heartbeats over significant periods of time.