Objective

In this project we are going to develop a common-path OCT system with self-adaptive tracking probe which will be used in endoscopic imaging and interventional ophthalmic microsurgery.

Introduction

Optical coherence tomography (OCT) is a noninvasive cross-sectional biomedical imaging modality with ultra-high resolution of a few micrometers [1]. However, current OCT systems generally suffer from very limited imaging depth range of only 1~3mm, which restricts its clinical applications when the sample surface variance is larger than the imaging depth range [1-2]. One very efficient way to solve this problem is to use adaptive ranging to detect the sample surface and then feed the information back to adjust the coherence gate and range on the reference arm [2-3]. For a common-path OCT system, the reference and sample signals share the same path [4] so that the reference offset can be changed directly by adjusting the distance between the fiber probe and the sample surface. In this work, we present a new method for surface recognition and feedback control based on an all-fiber common-path Fourier-domain OCT system (CP-FDOCT) with an improved surface location algorithm compared to the previous works in reference [2] and [3]. In our system, each A-scan (axial) data is analyzed in real-time with an edge-searching algorithm to recognize the sample surface, and then the surface position feeds back into the system to keep a fixed distance between the probe tip and the surface. Thereby the probe tracks the sample surface variance and the effective imaging depth can be largely extended up to the probe’s free-moving range.

Experiment

A schematic of the experimental set-up is shown in Fig. 1(a) where an SLED (EXS8410-2413) with 840nm central wavelength and ~40nm spectral FWHM is used as the light source, which gives a theoretical in-air resolution of ~8μm. C is a 50/50 coupler and only one branch on the right side is used as the common path for signal and reference. A right-angle cleaved fiber probe P is maintained on a controllable 3-D moving stage M, with A-scan (axial) in X direction and B-scan (lateral) in Y direction. The reference signal comes from the Fresnel reflection at the fiber probe end, and the sample signal and the reference are received by H, a high speed spectrometer (Ocean Optics HR-4000) with a CCD detector array with 3648 pixels and 699nm~891nm range. The A-scan signals are processed by the computer which then sends the control signal to M through GPIB interface.
 

Fig. 1 Self-adaptive CP-FDOCT system: (a) Experimental setup; (b) System flowchart;

Fig. 1(b) shows the system flowchart. The probe is required to keep a fixed distance D from the sample surface, and in the experiment we set D=200μm. After each A-scan, the signal collected through H is processed by the computer with the edge-searching algorithm, which finds the position of the first non-noise peak. The real distance from the probe end and the sample surface is determined to be d. The new probe position is thus given by x’=x-D+d, and then the computer sent corresponding controlling command to M to adjust the probe axial position before the next A-scan. In this way the probe can keep the distance D by tracking the surface variance of the sample. The probe position for each A-scan is saved and used to reconstruct the correct image from raw data after a complete B-scan.

Results

Using a phantom sample with 8-layers of highly curved surfaces, we first obtained a B-scan 2-D image by conventional fixed-reference method, shown as Fig. 2(a). The lateral scanning range is 2mm with a 5μm step size. The red arrows indicate the motion of the probe as well as its position. As one can see from the left part of Fig. 2(a), the CP-FDOCT has an effective working depth ~1mm and the layer structure on the “hill top” is very clear within this range. However, as expected due to the limited depth scanning range, the OCT image fades away as the probe is moved away from the top. Fig. 2(b) shows an improved image using the self-adaptive-reference method. As shown by the red arrows, the probe follows the falling of the surface as it obtains A-scans. The moving trace of probe is recorded and overlapped on Fig. 2(b) in red line, and the trace is consistent with the surface profile. By using the feedback control the probe is able to track the sample surface variance and the effective imaging depth was largely extended to the probe’s free-moving range. The surface location algorithm in reference [2] and [3] is based on the first and second moment calculation of the A-scan data, which depends much on the gain factor distribution inside the sample and cannot get the accurate surface position. Compared to moment calculation, edge-searching method gives much more accurate surface location and thus better for clinic applications such as interventional ophthalmic microsurgery.