40 research outputs found
Optimized Retinal Nerve Fiber Layer Segmentation Based On Optical Reflectivity And Birefringence For Polarization-Sensitive Optical Coherence Tomography
No full textSegmentation of the retinal nerve fiber layer (RNFL) from swept source polarization-sensitive optical coherence tomography (SS-PSOCT) images is required to determine RNFL thickness and calculate birefringence. Traditional RNFL segmentation methods based on image processing and boundary detection algorithms utilize only optical reflectivity contrast information, which is strongly affected by speckle noise. We present a novel approach to segment the retinal nerve fiber layer (RNFL) using SS-PSOCT images including both optical reflectivity and phase retardation information. The RNFL anterior boundary is detected based on optical reflectivity change due to refractive index difference between the vitreous and inner limiting membrane. The posterior boundary of the RNFL is a transition zone composed of birefringent axons extending from retinal ganglion cells and may be detected by a change in birefringence. A posterior boundary detection method is presented that segments the RNFL by minimizing the uncertainty of RNFL birefringence determined by a Levenberg-Marquardt nonlinear fitting algorithm. Clinical results from a healthy volunteer show that the proposed segmentation method estimates RNFL birefringence and phase retardation with lower uncertainty and higher continuity than traditional intensity-based approaches.Biomedical Engineerin
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Optical coherence tomography for retinal diagnostics
No full texttextOptical Coherence Tomography (OCT) is a non-invasive three-dimensional imaging technique. OCT synthesizes a cross-sectional image from a series of lateral adjacent depth scans, and with a two-dimensional scanning scheme, three-dimensional intensity image of sample can be constructed. Due to its non-invasive capability, OCT has been widely applied in ophthalmology, cardiology and dermatology; and in addition to three-dimensional intensity image construction, various functional OCT imaging techniques have been developed for clinical application. My research is focused on developing functional OCT systems for application in ophthalmology, including polarization-sensitive optical coherence tomography (PS-OCT) for retinal nerve fiber layer (RNFL) birefringence measurement and dual-wavelength photothermal optical coherence tomography (DWP-OCT) for microvasculature blood oxygen saturation (SO2) measurement. In the study, a single-mode-fiber based polarization-sensitive swept-source OCT (PS-SS-OCT) with polarization modulator, polarization-sensitive bulk-optics balanced detection module is constructed and polarization processing methods based on Stokes vectors are applied to determine birefringence. PS-OCT is able to provide human subject's RNFL thickness, phase retardation, and birefringence information. Degradation in the degree of polarization (DOP) along depth is investigated and its difference between four quadrants of RNFL (superior, temporal, inferior and nasal) indicates the structural property difference. DWP-OCT is a novel functional OCT system consisting of a phase-sensitive optical coherence tomography system (PhS-OCT) and two photothermal excitation lasers. PhS-OCT is based on a swept-source laser operating in the 1060 nm wavelength range; the two photothermal excitation lasers with wavelength 770 nm and 800 nm are intensity modulated at different frequencies. PhS-OCT probe beam and two photothermal excitation beams are combined and incident on the sample, optical pathlength (op) change on the sample introduced by two photothermal excitation beams are measured and used for blood SO2 estimation. A polarization microscope is proposed for future study. The polarization microscope is an imaging technique providing molecular structure and orientation based on probe light's polarization state information. The polarization microscope uses a wavelength tunable light source, and can achieve any incident polarization state by a retarder-rotator combination. Specimen's birefringence can be determined based on the changing of detected light amplitude.Electrical and Computer Engineerin
Understanding the societal, entrepreneurship and economic aspects of developing a Circular Economy in cities: a case study of Coventry in the UK
No full textOne of the points of agreement emerging from international environmental policy debates is that people’s choices, behaviors and lifestyles will play a vital role in achieving sustainable development (Biwei, 2012; Fleischmann, 2016). There is strong evidence of the importance of a working Circular Economy (CE) to address sustainability challenges but there are different accounts and narratives in the CE literature which can cause confusion when trying to define and understand the concept. Urbanisation coupled with the fact that cities are resource inefficient (Agudela-Vera 2012) has given rise to the emergence of Circular Cities such as, Amsterdam but research to date has had a strong emphasis on the “supply side” (business, policy, science) with little attention being paid to the people or “demand side” (social, consumer). It would therefore be helpful to develop a better understanding of the role that citizens and not just City governments can play in a Circular City. To address this the paper uses an illustrative example of Coventry in the UK to examine the strategies and policy actions that drive CE relevant grass roots citizen driven practices and innovations. Through the lens of this example the paper provides insights into the role that citizens could play in developing Circular Cities through citizen driven innovation mechanisms such as social enterprise. The paper concludes that we are lacking sufficient socio-economic evidence of impact on the “demand side” and provides recommendations for further research into the social and citizen driven innovation aspects of CE relevant activities in cities.Climate Design and Sustainabilit
A Deep Learning Approach to Vehicle Make and Model Recognition with Specification Matching
No full textVehicle Make and Model Recognition (VMMR) has risen to become a highly significant research area within the automobile sector in recent years. Specifically, it is beneficial in traffic analysis, vehicle analysis, and detection of crimes associated with vehicles, among other applications. A VMMR system with great accuracy and the ability to create dynamic real-time results helps save resources. For this recognition and classification task, a system that is sufficiently capable to handle the ambiguity and multiplicity that occurs between various makes and models needs to be implemented. This project aims to develop a vehicle model recognition system that can appropriately recognise and perform classification of vehicles into appropriate make and model classes they belong to with an attempt to match the accurately recognized vehicles with their standardized specifications. The author proposes three different models in order to address this challenge and develop a system that is more adaptive and responsive than previously proposed methods. The system is developed with these models (MobileNet-v2, ResNet50, VGG16) by training them with the train sets and evaluating the models by their accuracy and computational time. ResNet-50 outperforms the other models considering the accuracy and minimal trade-off with computational time. The ResNet-50 model is then incorporated into a GUI application which can be used for real life applications, this to displays the importance of the system to the automobile industry and intelligent transport systems
A coaxially focused multi-mode beam for optical coherence tomography imaging with extended depth of focus (Conference Presentation)
No full textA Multi-Objective Optimization Approach Based on an Enhanced Particle Swarm Optimization Algorithm With Evolutionary Game Theory
No full textDue to conflicts among objectives of multi-objective optimization (MO) problems, it remains challenging to gain high-quality Pareto fronts for different MO issues. Attempt to handle this challenge and obtain high-performance Pareto fronts, this paper proposes a novel MO optimizer via leveraging particle swarm optimization (PSO) with evolutionary game theory (EGT). Firstly, a modified self-adaptive PSO (MSAPSO) adopting a novel self-adaptive parameter adaption rule determined by the evolutionary strategy of EGT to tune the three key parameters of each particle is proposed in order to well balance the exploration and exploitation abilities of MSAPSO. Then, a parameter selection principle is provided to sufficiently guarantee convergence of MSAPSO followed after the analytical convergence investigation of this optimizer so as to assure convergence of the searched Pareto front toward the true Pareto front as far as possible. Subsequently, a MSAPSO-based MO optimizer is developed, in which an external archive is applied to preserve the searched non-dominated solutions and a circular sorting method is amalgamated with the elitist-saving method to update the external archive. Lastly, the performance of the proposed method is examined by 16 benchmark test functions against 4 well-known MOO methods. The simulation results reveal that the proposed method dominates its peers regarding the quality of the Pareto fronts for most of the studied benchmarks. Furthermore, the results of the non-parametric analysis confirm that the proposed method significantly outperforms its contenders at the confidential level of 95% over the 16 benchmarks
Degradation in the degree of polarization in human retinal nerve fiber layer
No full textUsing a fiber-based swept-source (SS) polarization-sensitive optical coherence tomography (PS-OCT) system, we investigate the degree of polarization (DOP) of light backscattered from the retinal nerve fiber layer (RNFL) in normal human subjects. Algorithms for processing data were developed to analyze the deviation in phase retardation and intensity of backscattered light in directions parallel and perpendicular to the nerve fiber axis (fast and slow axes of RNFL). Considering superior, inferior, and nasal quadrants, we observe the strongest degradation in the DOP with increasing RNFL depth in the temporal quadrant. Retinal ganglion cell axons in normal human subjects are known to have the smallest diameter in the temporal quadrant, and the greater degradation observed in the DOP suggests that higher polarimetric noise may be associated with neural structure in the temporal RNFL. The association between depth degradation in the DOP and RNFL structural properties may broaden the utility of PS-OCT as a functional imaging technique
Dispersion estimation and compensation in optical coherence tomography (Conference Presentation)
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