Distributed optical fiber biosensor based on optical frequency domain reflectometry.

In situ acquisition of spatial distribution of biochemical substances is important in cell analysis, cancer detection and other fields. Optical fiber biosensors can achieve label-free, fast and accurate measurements. However, current optical fiber biosensors only acquire single-point of biochemical substance content. In this paper, we present a distributed optical fiber biosensor based on tapered fiber in optical frequency domain reflectometry (OFDR) for the first time. To enhance evanescent field at a relative long sensing range, we fabricate a tapered fiber with a taper waist diameter of 6 µm and a total stretching length of 140 mm. Then the human IgG layer is coated on the entire tapered region by polydopamine (PDA) -assisted immobilization as the sensing element to achieve to sense anti-human IgG. We measure shifts of the local Rayleigh backscattering spectra (RBS) caused by the refractive index (RI) change of an external medium surrounding a tapered fiber after immunoaffinity interactions by using OFDR. The measurable concentration of anti-human IgG and RBS shift has an excellent linearity in a range from 0 ng/ml to 14 ng/ml with an effective sensing range of 50 mm. The concentration measurement limit of the proposed distributed biosensor is 2 ng/ml for anti-human IgG. Distributed biosensing based on OFDR can locate a concentration change of anti-human IgG with an ultra-high sensing spatial resolution of 680 µm. The proposed sensor has a potential to realize a micron-level localization of biochemical substances such as cancer cells, which will open a door to transform single-point biosensor to distributed biosensor.

Reconstruction error model of distributed shape sensing based on the reentered frame in OFDR.

At present, the reconstruction error of optical fiber shape sensing is commonly represented by Euclidean distance error. However, the Euclidian error of shape reconstruction will be dependent on the shape complexity, which depends on length, curvature and torsion. In this paper, we establish a reconstruction error model of distributed shape sensing in optical frequency domain reflectometry (OFDR) based on the Frenet-Serret frame and the error delivering theory, which illustrates the relationship between the reconstruction error and parameters such as curvature, torsion, fiber length and strain measurement error. We experimentally verify the feasibility and applicability of the proposed reconstruction error model by distributed optical fiber shape sensing system based on OFDR. The proposed reconstruction error model can provide a prediction of the maximal reconstruction error when the estimated range of curvature, torsion, fiber length of a shape needs to be reconstructed and strain measurement errors of OFDR system are known. It is very useful to judge whether the shape reconstruction error meets the requirement according to the shape to be reconstructed.

Analysis and reduction of noise-induced depolarization in catheter based polarization sensitive optical coherence tomography.

In catheter based polarization sensitive optical coherence tomography (PS-OCT), a optical fiber with a rapid rotation in the catheter can cause low signal-to-noise ratio (SNR), polarization state instability, phase change of PS-OCT signals and then heavy noise-induced depolarization, which has a strong impact on the phase retardation measurement of the sample. In this paper, we analyze the noise-induced depolarization and find that the effect of depolarization can be reduced by polar decomposition after incoherent averaging in the Mueller matrix averaging (MMA) method. Namely, MMA can reduce impact of noise on phase retardation mapping. We present a Monte Carlo method based on PS-OCT to numerically describe noise-induced depolarization effect and contrast phase retardation imaging results by MMA and Jones matrix averaging (JMA) methods. The peak signal to noise ratio (PSNR) of simulated images processed by MMA is higher than about 8.9 dB than that processed by JMA. We also implement experiments of multiple biological tissues using the catheter based PS-OCT system. From the simulation and experimental results, we find the polarization contrasts processed by the MMA are better than those by JMA, especially at areas with high depolarization, because the MMA can reduce effect of noise-induced depolarization on the phase retardation measurement.

Complete self-calibration compact binary magneto-optic rotator based Mueller matrix polarimetry.

Magneto-optic (MO) based Mueller matrix polarimetry (MMP) has several advantages of compact size, no-mechanical movement and high speed. Inaccuracies of components in the polarization state generator (PSG) optical parameters will influence the measurement accuracy of MMP. In this paper, we present a PSG self-calibration method in the compact MMP based on binary MO polarization rotators. Since PSG can generate enough numbers of non-degenerate polarization states, the optical parameters in PSG and the Mueller matrix of the sample can totally be numerically solved, which realizes a self-calibration in the PSG. Combining the previous self-calibration method in polarization state analyzer (PSA), we realize a complete self-calibration compact MO based MMP. Based on the numerical simulation results, the errors of measured phase retardance and optical axis of the sample decrease two to three orders of magnitude after applying the PSG self-calibration method. In experimental results of a variable retarder as a sample, the Euclidean distance of retardance between the measurement and reference curves comparing PSG self-calibration with no PSG self-calibration can be reduced from 0.035 rad to 0.033 rad and the Euclidean distance of optical axis can be reduced from 3.39° to 1.51°. Compared with the experimental results, the numerical simulation results more accurately verify the performance of the presented PSG self-calibration method without being influenced by other errors because the Mueller matrix of the sample is known and the error source only comes from these components in PSG.

Automatic lumen segmentation using uniqueness of vascular connected region for intravascular optical coherence tomography.

We present an automatic lumen segmentation method using uniqueness of connected region for intravascular optical coherence tomography (IVOCT), which can effectively remove the effect on lumen segmentation caused by blood artifacts. Utilizing the uniqueness of vascular wall on A-lines, we detect the A-lines shared by multiple connected regions, identify connected regions generated by blood artifacts using traversal comparison of connected regions' location, shared ratio and area ratio and then remove all artifacts. We compare these three methods by 216 challenging images with severe blood artifacts selected from clinical 1076 IVOCT images. The metrics of the proposed method are evaluated including Dice index, Jaccard index and accuracy of 94.57%, 90.12%, 98.02%. Compared with automatic lumen segmentation based on the previous morphological feature method and widely used dynamic programming method, the metrics of the proposed method are significantly enhanced, especially in challenging images with severe blood artifacts.

Three-dimensional spatial reconstruction of coronary arteries based on fusion of intravascular optical coherence tomography and coronary angiography.

We present a three-dimensional (3D) spatial reconstruction of coronary arteries based on fusion of intravascular optical coherence tomography (IVOCT) and digital subtraction angiography (DSA). Centerline of vessel in DSA images is exacted by multi-scale filtering, adaptive segmentation, morphology thinning and Dijkstra's shortest path algorithm. We apply the cross-correction between lumen shapes of IVOCT and DSA images and match their stenosis positions to realize co-registration. By matching the location and tangent direction of the vessel centerline of DSA images and segmented lumen coordinates of IVOCT along pullback path, 3D spatial models of vessel lumen are reconstructed. Using 1121 distinct positions selected from eight vessels, the correlation coefficient between 3D IVOCT model and DSA image in measuring lumen radius is 0.94% and 97.7% of the positions fall within the limit of agreement by Bland-Altman analysis, which means that the 3D spatial reconstruction IVOCT models and DSA images have high matching level.