Advanced Monte Carlo Simulation and Machine Learning for Frequency Domain Optical Coherence Tomography

Optical Coherence Tomography(OCT) is a popular, rapidly growing imaging technique with an increasing number of bio-medical applications due to its noninvasive nature. However, there are three major challenges in understanding and improving an OCT system: (1) Obtaining an OCT image is not easy. It either takes a real medical experiment or requires days of computer simulation. Without much data, it is difficult to study the physical processes underlying OCT imaging of different objects simply because there aren't many imaged objects. (2) Interpretation of an OCT image is also hard. This challenge is more profound than it appears. For instance, it would require a trained expert to tell from an OCT image of human skin whether there is a lesion or not. This is expensive in its own right, but even the expert cannot be sure about the exact size of the lesion or the width of the various skin layers. The take-away message is that analyzing an OCT image even from a high level would usually require a trained expert, and pixel-level interpretation is simply unrealistic. The reason is simple: we have OCT images but not their underlying ground-truth structure, so there is nothing to learn from. (3) The imaging depth of OCT is very limited (millimeter or sub-millimeter on human tissues). While OCT utilizes infrared light for illumination to stay noninvasive, the downside of this is that photons at such long wavelengths can only penetrate a limited depth into the tissue before getting back-scattered. To image a particular region of a tissue, photons first need to reach that region. As a result, OCT signals from deeper regions of the tissue are both weak (since few photons reached there) and distorted (due to multiple scatterings of the contributing photons). This fact alone makes OCT images very hard to interpret.

This thesis addresses the above challenges by successfully developing an advanced Monte Carlo simulation platform which is 10000 times faster than the state-of-the-art simulator in the literature, bringing down the simulation time from 360 hours to a single minute. This powerful simulation tool not only enables us to efficiently generate as many OCT images of objects with arbitrary structure and shape as we want on a common desktop computer, but it also provides us the underlying ground-truth of the simulated images at the same time because we dictate them at the beginning of the simulation. This is one of the key contributions of this thesis. What allows us to build such a powerful simulation tool includes a thorough understanding of the signal formation process, clever implementation of the importance sampling/photon splitting procedure, efficient use of a voxel-based mesh system in determining photon-mesh interception, and a parallel computation of different A-scans that consist a full OCT image, among other programming and mathematical tricks, which will be explained in detail later in the thesis.

Next we aim at the inverse problem: given an OCT image, predict/reconstruct its ground-truth structure on a pixel level. By solving this problem we would be able to interpret an OCT image completely and precisely without the help from a trained expert. It turns out that we can do much better. For simple structures we are able to reconstruct the ground-truth of an OCT image more than 98% correctly, and for more complicated structures (e.g., a multi-layered brain structure) we are looking at 93%. We achieved this through extensive uses of Machine Learning. The success of the Monte Carlo simulation already puts us in a great position by providing us with a great deal of data (effectively unlimited), in the form of (image, truth) pairs. Through a transformation of the high-dimensional response variable, we convert the learning task into a multi-output multi-class classification problem and a multi-output regression problem. We then build a hierarchy architecture of machine learning models (committee of experts) and train different parts of the architecture with specifically designed data sets. In prediction, an unseen OCT image first goes through a classification model to determine its structure (e.g., the number and the types of layers present in the image); then the image is handed to a regression model that is trained specifically for that particular structure to predict the length of the different layers and by doing so reconstruct the ground-truth of the image. We also demonstrate that ideas from Deep Learning can be useful to further improve the performance.

It is worth pointing out that solving the inverse problem automatically improves the imaging depth, since previously the lower half of an OCT image (i.e., greater depth) can be hardly seen but now becomes fully resolved. Interestingly, although OCT signals consisting the lower half of the image are weak, messy, and uninterpretable to human eyes, they still carry enough information which when fed into a well-trained machine learning model spits out precisely the true structure of the object being imaged. This is just another case where Artificial Intelligence (AI) outperforms human. To the best knowledge of the author, this thesis is not only a success but also the first attempt to reconstruct an OCT image at a pixel level. To even give a try on this kind of task, it would require fully annotated OCT images and a lot of them (hundreds or even thousands). This is clearly impossible without a powerful simulation tool like the one developed in this thesis.

Control of polarization signal distortion by frequency domain phase conjugation in optical fiber systems

Optical frequency domain phase conjugation (FDPC) is based on phase conjugation of spectrum of an input signal. It is equivalent to the phase conjugation and the time reversal of the temporal envelope of an input signal. The use of FDPC to control polarization signal distortion in birefringent optical fiber systems is proposed. Evolution of polarization signals in the system using midway FDPC is analyzed theoretically and simulated numerically. It is shown that the distortion of polarization signals can be controlled effectively by FDPC. The impairments due to dispersion and nonlinear effects can be suppressed simultaneously.

Designing a coupler for the intersatellite optical communication system

Coupling a single-mode laser diode with 200 mW to a single-mode fiber (SMF) through an orthonormal aspherical cylindrical lens and a GRIN lens for the intersatellite optical communication system is proposed and demonstrated. We experimentally studied how the coupling efficiency changes with the SMF's position displacement and axial angle variation, and obtained 80 mW output power at the end of the SMF, which shows that the coupling units have satisfied the designed request. (c) 2007 Elsevier GmbH. All rights reserved.

单块晶体集成的N×N纵横开关网络及其控制算法

设计了一种单块晶体集成的n×n纵横开关(Crossbar)网络。通过综合考虑晶体的双折射和全内双反射现象,以及晶体的电光效应,将构成n×n纵横开关网络的所有单元器件都集成到一块具有电光效应的双折射晶体上。同时,给出了该网络的控制算法,通过对开关工作状态的控制,可以实现任意输入输出通道之间的无阻塞连接。这种单块晶体集成的纵横开关网络具有能量损耗低、无阻塞、易安装、抗干扰等优点,适合于全光网络发展的需要。

Theoretical model for a periodically driven semiconductor laser subject to optical feedback from a microcantilever

We propose a theoretical model for analyzing the dynamics of a periodically driven semiconductor laser subject to optical feedback from a microcantilever. We numerically investigate the temporal evolution of the light intensity of the semiconductor laser, and we show the interspikes of the light intensity. These interspikes of light intensity are also demonstrated in our experiment. The validity of the theoretical model is verified. The observed phenomenon has a potential application for resonant sensing. (C) 2008 Optical Society of America.

One-shot parallel complex Fourier-domain optical coherence tomography using a spatial carrier frequency

We propose a novel method of one-shot parallel complex Fourier-domain optical coherence tomography using a spatial carrier frequency for full range imaging. The spatial carrier frequency is introduced into the 2-D spectral interferogram in the lateral direction by using a tilted reference wavefront. This spatial-carrier- contained 2-D spectral interferogram is recorded with one shot of a 2-D CCD camera, and is Fourier-transformed in the lateral direction to obtain a 2-D complex spectral interferogram by a spatial-carrier technique. A full-range tomogram is reconstructed from the 2-D complex spectral interferogram. The principle of this method is confirmed by cross-sectional imaging of a glass slip object. (c) 2008 Society of Photo-Optical Instrumentation Engineers.

Stabilization of optical Fabry-Perot sensor by active feedback control of diode laser

This paper presents the design and characterization of a fiber Fabry-Perot interferometer (FFPI) acoustic wave detector with its Q point being stabilized actively. The relationship between the reflectivity of the F-P cavity facets and cavity length was theoretically analyzed, and high visibility of 100% was realized by optimized design of the F-P cavity. To prevent the drifting of the Q point, a new stabilization method by actively feedback controlling of the diode laser is proposed and demonstrated, indicating the method is simple and easy operating. Measurement shows that good tracing of Q point was effectively realized. (c) 2008 Elsevier B.V. All rights reserved.

Electrical and optical investigations of beta-gallium oxide

An experimental investigation of the optical properties of β–gallium oxide has been carried out, covering the wavelength range 220-2500 nm.

The refractive index and birefringence have been determined to about ± 1% accuracy over the range 270-2500 nm, by the use of a technique based on the occurrence of fringes in the transmission of a thin sample due to multiple internal reflections in the sample (ie., the "channelled spectrum" of the sample.)

The optical absorption coefficient has been determined over the range 220 - 300 nm, which range spans the fundamental absorption edge of β – Ga₂O₃. Two techniques were used in the absorption coefficient determination: measurement of transmission of a thin sample, and measurement of photocurrent from a Schottky barrier formed on the surface of a sample. Absorption coefficient was measured over a range from 10 to greater than 10⁵, to an accuracy of better than ± 20%. The absorption edge was found to be strongly polarization-dependent.

Detailed analyses are presented of all three experimental techniques used. Experimentally determined values of the optical constants are presented in graphical form.

Characterization of a dissolved oxygen sensor made of plastic optical fiber coated with ruthenium-incorporated solgel

A dissolved oxygen sensor made of plastic optical fiber as the substrate and dichlorotris (1, 10-phenanthroline) ruthenium as a fluorescence indicator is studied. Oxygen quenching characteristics of both intensity and phase were measured; the obtained characteristics showed deviation from the linear relation described by the Stern-Volmer equation. A two-layer model is proposed to explain the deviation, and main parameters can be deduced with the model. (C) 2009 Optical Society of America