A Method of Drusen Measurement Based on the Geometry of Fundus Reflectance

BACKGROUND: The hallmarks of age-related macular degeneration, the leading cause of blindness in the developed world, are the subretinal deposits known as drusen. Drusen identification and measurement play a key role in clinical studies of this disease. Current manual methods of drusen measurement are laborious and subjective. Our purpose was to expedite clinical research with an accurate, reliable digital method. METHODS: An interactive semi-automated procedure was developed to level the macular background reflectance for the purpose of morphometric analysis of drusen. 12 color fundus photographs of patients with age-related macular degeneration and drusen were analyzed. After digitizing the photographs, the underlying background pattern in the green channel was leveled by an algorithm based on the elliptically concentric geometry of the reflectance in the normal macula: the gray scale values of all structures within defined elliptical boundaries were raised sequentially until a uniform background was obtained. Segmentation of drusen and area measurements in the central and middle subfields (1000 μm and 3000 μm diameters) were performed by uniform thresholds. Two observers using this interactive semi-automated software measured each image digitally. The mean digital measurements were compared to independent stereo fundus gradings by two expert graders (stereo Grader 1 estimated the drusen percentage in each of the 24 regions as falling into one of four standard broad ranges; stereo Grader 2 estimated drusen percentages in 1% to 5% intervals). RESULTS: The mean digital area measurements had a median standard deviation of 1.9%. The mean digital area measurements agreed with stereo Grader 1 in 22/24 cases. The 95% limits of agreement between the mean digital area measurements and the more precise stereo gradings of Grader 2 were -6.4 % to +6.8 % in the central subfield and -6.0 % to +4.5 % in the middle subfield. The mean absolute differences between the digital and stereo gradings 2 were 2.8 +/- 3.4% in the central subfield and 2.2 +/- 2.7% in the middle subfield. CONCLUSIONS: Semi-automated, supervised drusen measurements may be done reproducibly and accurately with adaptations of commercial software. This technique for macular image analysis has potential for use in clinical research

QUANTITATIVE METHODS AND DETECTION TECHNIQUES IN HYPERSPECTRAL IMAGING INVOLVING MEDICAL AND OTHER APPLICATIONS

This research using Hyperspectral imaging involves recognizing targets through spatial and spectral matching and spectral un-mixing of data ranging from remote sensing to medical imaging kernels for clinical studies based on Hyperspectral data-sets generated using the VFTHSI [Visible Fourier Transform Hyperspectral Imager], whose high resolution Si detector makes the analysis achievable. The research may be broadly classified into (I) A Physically Motivated Correlation Formalism (PMCF), which places both spatial and spectral data on an equivalent mathematical footing in the context of a specific Kernel and (II) An application in RF plasma specie detection during carbon nanotube growing process. (III) Hyperspectral analysis for assessing density and distribution of retinopathies like age related macular degeneration (ARMD) and error estimation enabling the early recognition of ARMD, which is treated as an ill-conditioned inverse imaging problem. The broad statistical scopes of this research are two fold- target recognition problems and spectral unmixing problems. All processes involve experimental and computational analysis of Hyperspectral data sets is presented, which is based on the principle of a Sagnac Interferometer, calibrated to obtain high SNR levels. PMCF computes spectral/spatial/cross moments and answers the question of how optimally the entire hypercube should be sampled and finds how many spatial-spectral pixels are required precisely for a particular target recognition. Spectral analysis of RF plasma radicals, typically Methane plasma and Argon plasma using VFTHSI has enabled better process monitoring during growth of vertically aligned multi-walled carbon nanotubes by instant registration of the chemical composition or density changes temporally, which is key since a significant correlation can be found between plasma state and structural properties. A vital focus of this thesis is towards medical Hyperspectral imaging applied to retinopathies like age related macular degeneration targets taken with a Fundus imager, which is akin to the VFTHSI. Detection of the constituent components in the diseased hyper-pigmentation area is also computed. The target or reflectance matrix is treated as a highly ill-conditioned spectral un-mixing problem, to which methodologies like inverse techniques, principal component analysis (PCA) and receiver operating curves (ROC) for precise spectral recognition of infected area. The region containing ARMD was easily distinguishable from the spectral mesh plots over the entire band-pass area. Once the location was detected the PMCF coefficients were calculated by cross correlating a target of normal oxygenated retina with the de-oxygenated one. The ROCs generated using PMCF shows 30% higher detection probability with improved accuracy than ROCs based on Spectral Angle Mapper (SAM). By spectral unmixing methods, the important endmembers/carotenoids of the MD pigment were found to be Xanthophyl and lutein, while β-carotene which showed a negative correlation in the unconstrained inverse problem is a supplement given to ARMD patients to prevent the disease and does not occur in the eye. Literature also shows degeneration of meso-zeaxanthin. Ophthalmologists may assert the presence of ARMD and commence the diagnosis process if the Xanthophyl pigment have degenerated 89.9%, while the lutein has decayed almost 80%, as found deduced computationally. This piece of current research takes it to the next level of precise investigation in the continuing process of improved clinical findings by correlating the microanatomy of the diseased fovea and shows promise of an early detection of this disease

Ground-based hyperspectral analysis of the urban nightscape

Airborne hyperspectral cameras provide the basic information to estimate the energy wasted skywards by outdoor lighting systems, as well as to locate and identify their sources. However, a complete characterization of the urban light pollution levels also requires evaluating these effects from the city dwellers standpoint, e.g. the energy waste associated to the excessive illuminance on walls and pavements, light trespass, or the luminance distributions causing potential glare, to mention but a few. On the other hand, the spectral irradiance at the entrance of the human eye is the primary input to evaluate the possible health effects associated with the exposure to artificial light at night, according to the more recent models available in the literature. In this work we demonstrate the possibility of using a hyperspectral imager (routinely used in airborne campaigns) to measure the ground-level spectral radiance of the urban nightscape and to retrieve several magnitudes of interest for light pollution studies. We also present the preliminary results from a field campaign carried out in the downtown of Barcelona.Postprint (author's final draft

Split-spectrum amplitude-decorrelation angiography with optical coherence tomography

Amplitude decorrelation measurement is sensitive to transverse flow and immune to phase noise in comparison to Doppler and other phase-based approaches. However, the high axial resolution of OCT makes it very sensitive to the pulsatile bulk motion noise in the axial direction. To overcome this limitation, we developed split-spectrum amplitude-decorrelation angiography (SSADA) to improve the signal-to-noise ratio (SNR) of flow detection. The full OCT spectrum was split into several narrower bands. Inter-B-scan decorrelation was computed using the spectral bands separately and then averaged. The SSADA algorithm was tested on in vivo images of the human macula and optic nerve head. It significantly improved both SNR for flow detection and connectivity of microvascular network when compared to other amplitude-decorrelation algorithms.National Institutes of Health (U.S.) (Grant R01 EY013516)National Institutes of Health (U.S.) (Grant R01-EY11289-26)United States. Air Force Office of Scientific Research (FA9550-10-1-0551

NON-INVASIVE IMAGE ENHANCEMENT OF COLOUR RETINAL FUNDUS IMAGES FOR A COMPUTERISED DIABETIC RETINOPATHY MONITORING AND GRADING SYSTEM

Diabetic Retinopathy (DR) is a sight threatening complication due to diabetes mellitus affecting the retina. The pathologies of DR can be monitored by analysing colour fundus images. However, the low and varied contrast between retinal vessels and the background in colour fundus images remains an impediment to visual analysis in particular in analysing tiny retinal vessels and capillary networks. To circumvent this problem, fundus fluorescein angiography (FF A) that improves the image contrast is used. Unfortunately, it is an invasive procedure (injection of contrast dyes) that leads to other physiological problems and in the worst case may cause death. The objective of this research is to develop a non-invasive digital Image enhancement scheme that can overcome the problem of the varied and low contrast colour fundus images in order that the contrast produced is comparable to the invasive fluorescein method, and without introducing noise or artefacts. The developed image enhancement algorithm (called RETICA) is incorporated into a newly developed computerised DR system (called RETINO) that is capable to monitor and grade DR severity using colour fundus images. RETINO grades DR severity into five stages, namely No DR, Mild Non Proliferative DR (NPDR), Moderate NPDR, Severe NPDR and Proliferative DR (PDR) by enhancing the quality of digital colour fundus image using RETICA in the macular region and analysing the enlargement of the foveal avascular zone (F AZ), a region devoid of retinal vessels in the macular region. The importance of this research is to improve image quality in order to increase the accuracy, sensitivity and specificity of DR diagnosis, and to enable DR grading through either direct observation or computer assisted diagnosis system

Engineering data compendium. Human perception and performance. User's guide

The concept underlying the Engineering Data Compendium was the product of a research and development program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design and military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from the existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by systems designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is the first volume, the User's Guide, containing a description of the program and instructions for its use

Diagnostic assessment of glaucoma and non-glaucomatous optic neuropathies via optical texture analysis of the retinal nerve fibre layer

The clinical diagnostic evaluation of optic neuropathies relies on the analysis of the thickness of the retinal nerve fibre layer (RNFL) by optical coherence tomography (OCT). However, false positives and false negatives in the detection of RNFL abnormalities are common. Here we show that an algorithm integrating measurements of RNFL thickness and reflectance from standard wide-field OCT scans can be used to uncover the trajectories and optical texture of individual axonal fibre bundles in the retina and to discern distinctive patterns of loss of axonal fibre bundles in glaucoma, compressive optic neuropathy, optic neuritis and non-arteritic anterior ischaemic optic neuropathy. Such optical texture analysis can detect focal RNFL defects in early optic neuropathy, as well as residual axonal fibre bundles in end-stage optic neuropathy that were indiscernible by conventional OCT analysis and by red-free RNFL photography. In a diagnostic-performance study, optical texture analysis of the RNFL outperformed conventional OCT in the detection of glaucoma, as defined by visual-field testing or red-free photography. Our findings show that optical texture analysis of the RNFL for the detection of optic neuropathies is highly sensitive and specific