Dynamic-range Compression and Contrast Enhancement in Swept Source Optical Coherence Tomography

Abstract

Optical coherence tomography(OCT) has been widely used in clinical applications. Using the Fourier domain technique based on a high speed wavelength swept source, swept source OCT (SSOCT) has increasingly gained attention for its relatively simple system structure and high imaging speed [1]. In spite of all the advantages of SSOCT, there are still some impediments that hinder the application in clinic. Since the light strongly attenuates in biological tissues, the image quality of optical coherence tomography (OCT) decreases rapidly with imaging depth. Numerical methods have been reported to compensate for the signal decay based on analysis of OCT signals [2-5] to increase the contrast and quality of deep tissue image. However, considering that the commonly used analog to digital converter of an SSOCT system is hard to fulfil the wide range of the backscattered OCT signal [6], weak light signal from deep tissue might be embedded in the quantization noise of the analog to digital converter. Hence, the numerical methods cannot digitally recover the weak signals submerged in the background noise.
In this paper, we designed and used a frequency gain compensation amplifier to amplify the electrical signal from a photodetector and compensate for the signal attenuation in swept source OCT. With this amplifier, we can compress the dynamic range of the detected signal for superior analog to digital conversion and image display capability.
As illustrated in Fig. 1(A), (C) and (E), the signal intensity and the contrast of the OCT image decay with increasing depth resulting in low visibility in deep tissue. While the OCT images after compensation present an improved visibility of the deep structure and a more uniform contrast through the image as shown in Fig. 1(B), (D), and (F), demonstrating that this cost-efficient technique can effectively enhance the contrast of the deep tissue image.

REFERENCES
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Speaker

JUN ZHANG
School of Electronics and Information Technology, Sun Yat-Sen University
China

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