Incorrect placement of the needle causes medical complications in the epidural block, such as dural puncture or spinal cord injury. This study proposes a system which combines an optical coherence tomography (OCT) imaging probe with an automatic identification (AI) system to objectively identify the position of the epidural needle tip. The automatic identification system uses three features as image parameters to distinguish the different tissue by three classifiers. Finally, we found that the support vector machine (SVM) classifier has highest accuracy, specificity, and sensitivity, which reached to 95%, 98%, and 92%, respectively.
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.