Molecular imaging using fluorescence spectroscopy-based techniques is generally inefficient due to the low quantum yield of most naturally occurring biomolecules. Current fluorescence imaging techniques tag these biomolecules chemically or through genetic manipulation, increasing the complexity of the system. A technique capable of imaging these biomolecules without modifying the chromophore and/or its environment could provide vital biometric parameters and unique insights into various biological processes at a molecular level. Pump probe spectroscopy has been used extensively to study the molecular properties of poorly fluorescing biomolecules, because it utilizes the known absorption spectrum of these chromophores. Optical Coherence Tomography (OCT) is an optical imaging modality that harnesses the power of low coherence interferometry to measure the 3-D spatially resolved reflectivity of a tissue sample. We plan to develop a new molecular imaging modality that combines these techniques to provide 3-D, highresolution molecular images of various important biomolecules. The system uses a Fourier domain OCT setup with a modified sample arm that combines the "pump" and "probe" beams. The pump beam drives the molecules from the ground state to excited state and the probe interrogates the population change due to the pump and is detected interferometrically. The pump and the probe beam wavelengths are optimized to maximize absorption at the pump wavelength and maximize the penetration depth at the probe wavelength. The pump-probe delay can be varied to measure the rate at which the excited state repopulates the ground state, i.e., the ground state recovery time. The ground state recovery time varies for different chromophores and can potentially be used to identify different biomolecules. The system was designed and optimized to increase the SNR of the PPOCT signals. It was tested by imaging hemoglobin and melanin samples and yielded encouraging results. Potential applications of imaging hemoglobin using this technique include the mapping of tissue microvasculature and measuring blood-oxygen saturation levels. These applications could be used to identify hypoxic areas in tissue. Melanin imaging can provide means of demarcation of melanoma in various organs such as skin, eye and intestines.

A detailed understanding of the corneal biomechanical response is an important prerequisite to understanding corneal diseases such as keratoconus and for placing the empirical equations used in refractive surgery on a physical basis. We have assembled a combined nonlinear optical microscopy (NLOM) and optical coherence microscopy (OCM) imaging system to simultaneously capture coregistered volumetric images of corneal morphology and biochemistry. Fudicial markers visible in the OCM volume enabled the calculation of strains for multiple depth layers in rabbit cornea. The results revealed a depth dependent strain distribution, with smaller strains in the anterior stroma and larger strains in the posterior stroma. The stress-strain curves can be grouped readily by depth into three groups: anterior (~20%), transitional mid (~40%), and posterior (~40%). Cross-sectional images of collagen lamellae, visible in NLOM, showed inhomogeneous collagen structure and its response to intraocular pressure along the anterior-posterior direction. The inhomogeneities correlate well with the noted heterogeneous corneal mechanical properties. The combined NLOM-OCM system can measure corneal microstructure and mechanical response uniquely, thus providing a microstructural understanding of corneal response to changes of collagen structure.

Glaucoma is the second leading cause of blindness worldwide after cataract. Retinal nerve fiber layer thickness (RNFLT), phase retardation, and birefringence measured by Polarization Sensitive Optical Coherence Tomography (PS-OCT) have been used for glaucoma diagnosis. We first investigated two different image registration algorithms, a mutual information (MI) based algorithm and a log-polar transform cross-correlation (LPCC) based algorithm, on both human and non-human primate models. We evaluated the effects of image registration on longitudinal analysis of RNFLT in non-human primates using PS-OCT. Then, we investigated thickness, phase retardation, birefringence, and reflectance of the retinal nerve fiber layer as measured by PS-OCT in normal and glaucomatous non-human primates in a longitudinal study. We defined a new Reflectance Index (RI) and demonstrated that it might be an earlier indicator of glaucoma onset than RNFLT, phase retardation, or birefringence. Finally, we validated this finding on cross-sectional clinical study on human eyes measured by PS-OCT and RTVue OCT. For the data measured by PS-OCT, we showed that for distinguishing between glaucomatous and healthy eyes, as well as for distinguishing between glaucoma suspect and healthy eyes, our new normalized RNFL reflectance index (NRRI) performs significantly better than phase retardation and birefringence. The performances of NRRI and RNFL thickness in both conditions were statistically indistinguishable in this study, which is likely due to the limited sample size. For the data measured by RTVue OCT, the performances of NRRI and RNFL thickness were statistically indistinguishable for distinguishing between glaucomatous and healthy eyes. NRRI performs significantly better than RNFL thickness for distinguishing between glaucoma suspect and healthy eyes. NRRI also performs significantly better than temporal, superior, nasal, inferior and temporal (TSNIT) average and nerve fiber indicator (NFI) from GDx VCC for distinguishing between glaucoma suspect and healthy eyes. NRRI is a promising parameter for distinguishing glaucoma suspect and healthy eyes and may indicate disease in the pre-perimetric stage. / text

Abstract Cardiovascular disease is one of the leading causes of death in Canada. Atherosclerosis is considered the primary cause for cardiovascular disease. Optical coherence tomography (OCT) provides a means to minimally invasive imaging and assessment of textural features of atherosclerotic plaque. However, detecting atherosclerotic plaque by visual inspection from Optical Coherence Tomography (OCT) images is usually difficult. Therefore we developed unsupervised segmentation algorithms to automatically detect atherosclerosis plaque from OCT images. We used three different clustering methods to identify atherosclerotic plaque automatically from OCT images. Our method involves data preprocessing of raw OCT images, feature selection and texture feature extraction using the Spatial Gray Level Dependence Matrix method (SGLDM), and the application of three different clustering techniques: K-means, Fuzzy C-means and Gustafson-Kessel algorithms to segment the plaque regions from OCT images and to map the cluster regions (background, vascular tissue, OCT degraded signal region and Atherosclerosis plaque) from the feature-space back to the original preprocessed OCT image. We validated our results by comparing our segmented OCT images with actual photographic images of vascular tissue with plaque. / October 2015

This study investigates three high resolution optical imaging modalities to better detect and diagnose skin cancer. The ideal high resolution optical imaging system can visualize pre-malignant tissue growth non-invasively with resolution comparable to histology. I examined 3 modalities which approached this goal. The first method examined was high magnification microscopy of thin stained tissue sections, together with a statistical analysis of nuclear chromatin patterns termed Karyometry. This method has subcellular resolution, but it necessitates taking a biopsy at the desired tissue site and imaging the tissue ex-vivo. My part of this study was to develop an automated nuclear segmentation algorithm to segment cell nuclei in skin histology images for karyometric analysis. The results of this algorithm were compared to hand segmented cell nuclei in the same images, and it was concluded that the automated segmentations can be used for karyometric analysis.The second optical imaging modality I investigated was Optical Coherence Tomography (OCT). OCT is analogous to ultrasound, in which sound waves are delivered into the body and the echo time and reflected signal magnitude are measured. Due to the fast speed of light and detector temporal integration times, low coherence interferometry is needed to gate the backscattered light. OCT acquires cross sectional images, and has an axial resolution of 1-15 µm (depending on the source bandwidth) and a lateral resolution of 10-20 µm (depending on the sample arm optics). While it is not capable of achieving subcellular resolution, it is a non-invasive imaging modality. OCT was used in this study to evaluate skin along a continuum from normal to sun damaged to precancer. I developed algorithms to detect statistically significant differences between images of sun protected and sun damaged skin, as well as between undiseased and precancerous skin.An Optical Coherence Microscopy (OCM) endoscope was developed in the third portion of this study. OCM is a high resolution en-face imaging modality. It is a hybrid system that combines the principles of confocal microscopy with coherence gating to provide an increased imaging depth. It can also be described as an OCT system with a high NA objective. Similar to OCT, the axial resolution is determined by the source center wavelength and bandwidth. The NA of the sample arm optics determines the lateral resolution, usually on the order of 1-5 µm. My effort on this system was to develop a handheld endoscope. To my knowledge, an OCM endoscope has not been developed prior to this work. An image of skin was taken as a proof of concept. This rigid handheld OCM endoscope will be useful for applications ranging from minimally invasive surgical imaging to non-invasively assessing dysplasia and sun damage in skin.

More and more researchers and clinicians are looking to molecular sensing to predict how cells will behave, seeking the answers to questions like "will these tumor cells become malignant?" or "how will these cells respond to chemotherapy?" Optical methods are attractive for answering these questions because optical radiation is safer and less expensive than alternative methods, such as CT which uses X-ray radiation, PET/SPECT which use gamma radiation, or MRI which is expensive and only available in a hospital setting. In this dissertation, three distinct optical methods are explored to detect at the molecular level: optical coherence tomography (OCT), laser-induced fluorescence (LIF), and optical polarimetry. OCT has the capability to simultaneously capture anatomical information as well as molecular information using targeted contrast agents such as gold nanoshells. LIF is less useful for capturing anatomical information, but it can achieve significantly better molecular sensitivity with the use of targeted fluorescent dyes. Optical polarimetry has potential to detect the concentration of helical molecules, such as glucose. All of these methods are noninvasive or minimally invasive.The work is organized into four specific aims. The first is the design and implementation of a fast, high resolution, endoscopic OCT system to facilitate minimally invasive mouse colon imaging. The second aim is to demonstrate the utility of this system for automatically identifying tumor lesions based on tissue microstructure. The third is to demonstrate the use of contrast agents to detect molecular expression using OCT and LIF. The last aim is to demonstrate a new method based on optical polarimetry for noninvasive glucose sensing.

Measuring the Mueller matrix with optical coherence tomography (OCT) makes it possible to acquire the complete polarization properties of scattering media with three-dimensional spatial resolution. We first proved that the measured degree-of-polarization (DOP) of the backscattered light by OCT remains unity-a conclusion that validated the use of Jones calculus in OCT. A multi-channel Mueller-matrix OCT system was then built to measure the Jones-matrix, which can be transformed into a Mueller matrix, images of scattering biological tissues accurately with single depth scan. We showed that when diattenuation is negligible, the round-trip Jones matrix represents a linear retarder, which is the foundation of conventional PS-OCT, and can be calculated with a single incident polarization state although the one-way Jones matrix generally represents an elliptical retarder; otherwise, two incident polarization states are needed. We discovered the transpose symmetry in the roundtrip Jones matrix, which is critical for eliminating the arbitrary phase difference between the two measured Jones vectors corresponding to the two incident polarization states to yield the correct Jones matrix. We investigated the various contrast mechanisms provided by Mueller-matrix OCT. Our OCT system for the first time offers simultaneously comprehensive polarization contrast mechanisms including the amplitude of birefringence, the orientation of birefringence, and the diattenuation in addition to the polarization-independent intensity contrast, all of which can be extracted from the measured Jones or the equivalent Mueller matrix. The experimental results obtained from rat skin samples, show that Mueller OCT provides complementary structural and functional information on biological samples and reveal that polarization contrast is more sensitive to thermal degeneration of biological tissues than amplitude-based contrast. Finally, an optical-fiber-based multi-channel Mueller-matrix OCT was built and a new rigorous algorithm was developed to retrieve the calibrated polarization properties of a sample. For the first time to our knowledge, fiber-based polarization-sensitive OCT was dynamically calibrated to eliminate the polarization distortion caused by the single-mode optical fiber in the sample arm, thereby overcoming a key technical impediment to the application of optical fibers in this technology.

The objective of this study is to apply digital image processing (DIP) techniques to optical coherence tomography (OCT) images and develop computer-based non-subjective quantitative analysis, which can be used as diagnostic aids in early detection of dental caries. This study first compares speckle reduction effects on raw OCT image data by implementing spatial-domain and transform-domain speckle filtering. Then region-based contour search and global thresholding techniques examine digital OCT images with possible lesions to identify and highlight the presence of features indicating early stage dental caries. The outputs of these processes, which explore the combination of image restoration and segmentation, can be used to distinguish lesion from normal tissue and determine the characteristics prior to, during, and following treatments. The combination of image processing and analysis techniques in this thesis shows potential of detecting early stage caries lesion successfully.

Obtaining higher depth of imaging is an important goal in Optical Coherence Tomography (OCT) systems. One of the main factors that affect the depth of OCT imaging is the presence of noise. That’s why the study of noise statistics is an important problem. In the first part of this thesis we obtain an empirical estimate of the second order statistics of noise by using a sequence of Time domain (TD) OCT images. These estimates confirm the non-stationary nature of noise in TD-OCT. In the second part of the thesis these estimates are used to design a depth-dependent matched filter to maximize the Signal-to-Noise Ratio (SNR) and increase the Contrast-to-Noise Ratio (CNR) in TD-OCT. By applying our filter to TD-OCT images of both vascular rabbit tissue and a human tooth, both SNR and CNR were increased and a higher imaging depth was achieved.

About 50% of cancer patients are treated with X-ray radiation therapy; however, with current treatment feedback, the effects and the efficacy of the treatment are generally detected several weeks/months after treatment completion. This makes the adjustment of the treatment based on early response, and identification of non-responding patients, nearly impossible. In this thesis a novel method combining optical coherence tomography and a gamut of image analysis methods is explored as a potential approach to detecting tissue variability. Applying texture analysis to the optical coherence tomography images may allow for the tracking of radiation therapy induced cell microstructural changes in cancer patients and help in the adjustment of treatment based on early response.