329 research outputs found
Human retinal oximetry using hyperspectral imaging
The aim of the work reported in this thesis was to investigate the possibility of
measuring human retinal oxygen saturation using hyperspectral imaging. A direct
non-invasive quantitative mapping of retinal oxygen saturation is enabled by
hyperspectral imaging whereby the absorption spectra of oxygenated and deoxygenated
haemoglobin are recorded and analysed. Implementation of spectral
retinal imaging thus requires ophthalmic instrumentation capable of efficiently
recording the requisite spectral data cube. For this purpose, a spectral retinal imager
was developed for the first time by integrating a liquid crystal tuneable filter into the
illumination system of a conventional fundus camera to enable the recording of
narrow-band spectral images in time sequence from 400nm to 700nm. Postprocessing
algorithms were developed to enable accurate exploitation of spectral
retinal images and overcome the confounding problems associated with this technique
due to the erratic eye motion and illumination variation.
Several algorithms were developed to provide semi-quantitative and quantitative
oxygen saturation measurements. Accurate quantitative measurements necessitated an
optical model of light propagation into the retina that takes into account the
absorption and scattering of light by red blood cells. To validate the oxygen saturation
measurements and algorithms, a model eye was constructed and measurements were
compared with gold-standard measurements obtained by a Co-Oximeter. The
accuracy of the oxygen saturation measurements was (3.31%± 2.19) for oxygenated
blood samples. Clinical trials from healthy and diseased subjects were analysed and
oxygen saturation measurements were compared to establish a merit of certain retinal
diseases. Oxygen saturation measurements were in agreement with clinician
expectations in both veins (48%±9) and arteries (96%±5). We also present in this
thesis the development of novel clinical instrument based on IRIS to perform retinal
oximetry.Al-baath University, Syri
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Astigmatism and Pseudoaccommodation in Pseudophakic Eyes
noAdvanced IOLs with circumferential zones of different power provide pseudoaccommodation. We investigated the potential for power variation with meridian, namely astigmatism, to provide pseudo-accommodation. With appropriate power and axis orientations, acceptable pseudo-accommodation can be achieved
Retinal Fundus Image Analysis for Diagnosis of Glaucoma: A Comprehensive Survey
© 2016 IEEE. The rapid development of digital imaging and computer vision has increased the potential of using the image processing technologies in ophthalmology. Image processing systems are used in standard clinical practices with the development of medical diagnostic systems. The retinal images provide vital information about the health of the sensory part of the visual system. Retinal diseases, such as glaucoma, diabetic retinopathy, age-related macular degeneration, Stargardt's disease, and retinopathy of prematurity, can lead to blindness manifest as artifacts in the retinal image. An automated system can be used for offering standardized large-scale screening at a lower cost, which may reduce human errors, provide services to remote areas, as well as free from observer bias and fatigue. Treatment for retinal diseases is available; the challenge lies in finding a cost-effective approach with high sensitivity and specificity that can be applied to large populations in a timely manner to identify those who are at risk at the early stages of the disease. The progress of the glaucoma disease is very often quiet in the early stages. The number of people affected has been increasing and patients are seldom aware of the disease, which can cause delay in the treatment. A review of how computer-aided approaches may be applied in the diagnosis and staging of glaucoma is discussed here. The current status of the computer technology is reviewed, covering localization and segmentation of the optic nerve head, pixel level glaucomatic changes, diagonosis using 3-D data sets, and artificial neural networks for detecting the progression of the glaucoma disease
Analysis of Retinal Image Data to Support Glaucoma Diagnosis
Fundus kamera je ĆĄiroce dostupnĂ© zobrazovacĂ zaĆĂzenĂ, kterĂ© umoĆŸĆuje relativnÄ rychlĂ© a nenĂĄkladnĂ© vyĆĄetĆenĂ zadnĂho segmentu oka â sĂtnice. Z tÄchto dĆŻvodĆŻ se mnoho vĂœzkumnĂœch pracoviĆĄĆ„ zamÄĆuje prĂĄvÄ na vĂœvoj automatickĂœch metod diagnostiky nemocĂ sĂtnice s vyuĆŸitĂm fundus fotografiĂ. Tato dizertaÄnĂ prĂĄce analyzuje souÄasnĂœ stav vÄdeckĂ©ho poznĂĄnĂ v oblasti diagnostiky glaukomu s vyuĆŸitĂm fundus kamery a navrhuje novou metodiku hodnocenĂ vrstvy nervovĂœch vlĂĄken (VNV) na sĂtnici pomocĂ texturnĂ analĂœzy. Spolu s touto metodikou je navrĆŸena metoda segmentace cĂ©vnĂho ĆeÄiĆĄtÄ sĂtnice, jakoĆŸto dalĆĄĂ hodnotnĂœ pĆĂspÄvek k souÄasnĂ©mu stavu ĆeĆĄenĂ© problematiky. Segmentace cĂ©vnĂho ĆeÄiĆĄtÄ rovnÄĆŸ slouĆŸĂ jako nezbytnĂœ krok pĆedchĂĄzejĂcĂ analĂœzu VNV. Vedle toho prĂĄce publikuje novou volnÄ dostupnou databĂĄzi snĂmkĆŻ sĂtnice se zlatĂœmi standardy pro ĂșÄely hodnocenĂ automatickĂœch metod segmentace cĂ©vnĂho ĆeÄiĆĄtÄ.Fundus camera is widely available imaging device enabling fast and cheap examination of the human retina. Hence, many researchers focus on development of automatic methods towards assessment of various retinal diseases via fundus images. This dissertation summarizes recent state-of-the-art in the field of glaucoma diagnosis using fundus camera and proposes a novel methodology for assessment of the retinal nerve fiber layer (RNFL) via texture analysis. Along with it, a method for the retinal blood vessel segmentation is introduced as an additional valuable contribution to the recent state-of-the-art in the field of retinal image processing. Segmentation of the blood vessels also serves as a necessary step preceding evaluation of the RNFL via the proposed methodology. In addition, a new publicly available high-resolution retinal image database with gold standard data is introduced as a novel opportunity for other researches to evaluate their segmentation algorithms.
Generalizable automated pixel-level structural segmentation of medical and biological data
Over the years, the rapid expansion in imaging techniques and equipments has driven the demand for more automation in handling large medical and biological data sets. A wealth of approaches have been suggested as optimal solutions for their respective imaging types. These
solutions span various image resolutions, modalities and contrast (staining) mechanisms. Few approaches generalise well across multiple image types, contrasts or resolution.
This thesis proposes an automated pixel-level framework that addresses 2D, 2D+t and 3D
structural segmentation in a more generalizable manner, yet has enough adaptability to address
a number of specific image modalities, spanning retinal funduscopy, sequential
fluorescein angiography and two-photon microscopy.
The pixel-level segmentation scheme involves: i ) constructing a phase-invariant orientation field of the local spatial neighbourhood; ii ) combining local feature maps with intensity-based
measures in a structural patch context; iii ) using a complex supervised learning process to interpret the combination of all the elements in the patch in order to reach a classification decision. This has the advantage of transferability from retinal blood vessels in 2D to neural structures in 3D.
To process the temporal components in non-standard 2D+t retinal angiography sequences, we first introduce a co-registration procedure: at the pairwise level, we combine projective
RANSAC with a quadratic homography transformation to map the coordinate systems between any two frames. At the joint level, we construct a hierarchical approach in order for each individual frame to be registered to the global reference intra- and inter- sequence(s). We then take a non-training approach that searches in both the spatial neighbourhood of each pixel and the filter output across varying scales to locate and link microvascular centrelines to (sub-)
pixel accuracy. In essence, this \link while extract" piece-wise segmentation approach combines the local phase-invariant orientation field information with additional local phase estimates to obtain a soft classification of the centreline (sub-) pixel locations.
Unlike retinal segmentation problems where vasculature is the main focus, 3D neural segmentation requires additional
exibility, allowing a variety of structures of anatomical importance yet with different geometric properties to be differentiated both from the background and against other structures. Notably, cellular structures, such as Purkinje cells, neural dendrites and interneurons, all display certain elongation along their medial axes, yet each class has a characteristic shape captured by an orientation field that distinguishes it from other structures. To take this
into consideration, we introduce a 5D orientation mapping to capture these orientation properties.
This mapping is incorporated into the local feature map description prior to a learning
machine. Extensive performance evaluations and validation of each of the techniques presented in this thesis is carried out. For retinal fundus images, we compute Receiver Operating Characteristic (ROC) curves on existing public databases (DRIVE & STARE) to assess and compare our algorithms with other benchmark methods. For 2D+t retinal angiography sequences, we compute the error metrics ("Centreline Error") of our scheme with other benchmark methods.
For microscopic cortical data stacks, we present segmentation results on both surrogate data with known ground-truth and experimental rat cerebellar cortex two-photon microscopic tissue stacks.Open Acces
Investigation of the Retinal Biomarkers of Alzheimerâs Disease and Atherosclerosis Using Hyperspectral Images
Le fait que l'oeil puisse ĂȘtre visualisĂ© de maniĂšre non invasive ouvre des possibilitĂ©s de mesure de biomarqueurs pour le diagnostic de conditions Ă long terme. Selon de nombreuses Ă©tudes, plusieurs maladies cardiovasculaires et neurodĂ©gĂ©nĂ©ratives telles que la maladie dâAlzheimer (AD) et lâathĂ©rosclĂ©rose (ATH) se manifestent dans la rĂ©tine sous forme de modifications morphologiques pathologiques et / ou vasculaires. Des mĂ©thodes d'imagerie oculaire en deux dimensions et des techniques de tomographie par cohĂ©rence optique (OCT) en trois dimensions ont Ă©tĂ© dĂ©veloppĂ©es pour fournir des descriptions des structures rĂ©tiniennes. Cependant, les images acquises par ces techniques permettent principalement de mesurer les caractĂ©ristiques spatiales et pas la variance relative de lâintensitĂ© des pixels sur diffĂ©rentes longueurs dâonde, de sorte que dâimportantes caractĂ©ristiques liĂ©es aux tissus peuvent encore rester Ă dĂ©couvrir.
Dans cette Ă©tude, une camĂ©ra rĂ©tinienne mĂ©tabolique hyperspectrale (MHRC) a Ă©tĂ© utilisĂ©e pour permettre l'acquisition d'une sĂ©rie d'images rĂ©tiniennes obtenues Ă des longueurs d'onde spĂ©cifiques couvrant le spectre du visible au proche infrarouge (NIR). Dans cette technique, le facteur de transmission, l'absorption et la diffusion de la lumiĂšre sont reflĂ©tĂ©s dans le spectre de la lumiĂšre Ă©mise par le tissu. Par consĂ©quent, non seulement les caractĂ©ristiques spatiales communes mais Ă©galement les « signatures spectrales » de biomolĂ©cules pourraient ĂȘtre rĂ©vĂ©lĂ©es. Cela aide Ă trouver une plus grande variĂ©tĂ© de caractĂ©ristiques spatiales / spectrales pour une investigation plus prĂ©cise des biomarqueurs rĂ©tiniens des maladies.
En ce qui concerne les coĂ»ts et les limites associĂ©s aux diagnostics actuels de lâAD et de lâATH, le but de cette thĂšse Ă©tait dâanalyser le contenu en informations dâimages rĂ©tiniennes hyperspectrales riches en donnĂ©es dans le but de caractĂ©riser des informations discriminantes cachĂ©es liĂ©es aux tissus afin dâidentifier des biomarqueurs possibles de ces deux maladies. Ă cette fin, une combinaison de caractĂ©ristiques vasculaires et de mesures de textures spatiales-spectrales ont Ă©tĂ© extraites de diffĂ©rentes rĂ©gions anatomiques de la rĂ©tine.
Dans le contexte de la maladie d'Alzheimer, des images rétiniennes de 20 cas présentant une altération cognitive et de 26 cas normaux cognitivement ont été acquises à l'aide de la caméra MHRC. Le statut amyloïde cérébral a été déterminé à partir de lectures binaires effectuées par un panel de 3 experts noteurs ayant participé à des études de TEP au 18F-Florbetaben.
Des caractĂ©ristiques de lâimage rĂ©tinienne ont Ă©tĂ© calculĂ©es, notamment la tortuositĂ© et le diamĂštre des vaisseaux, ainsi que les mesures de textures spatiales-spectrales sur les artĂ©rioles, les veinules et le tissu environnant. Les veinules rĂ©tiniennes des sujets amyloĂŻdes positifs (AÎČ +) ont prĂ©sentĂ© une tortuositĂ© moyenne plus Ă©levĂ©e par rapport aux sujets amyloĂŻdes nĂ©gatifs (AÎČ-). Le diamĂštre artĂ©riolaire des sujets AÎČ + s'est avĂ©rĂ© supĂ©rieur Ă celui des sujets AÎČ- dans une zone adjacente Ă la tĂȘte du nerf optique. De plus, une diffĂ©rence significative entre les mesures de texture construites sur les artĂ©rioles rĂ©tiniennes et leurs rĂ©gions adjacentes a Ă©tĂ© observĂ©e chez les sujets AÎČ + par rapport aux AÎČ-.
Dans le contexte de l'ATH, 60 images rétiniennes de 30 ATH probables sur le plan clinique et 30 cas de contrÎle ont été acquises. Les critÚres d'inclusion pour les sujets souffrant d'ATH comprenaient: l'infarctus du myocarde; angiographie coronaire montrant au moins une sténose coronaire (plus de 50%); et / ou une angioplastie coronaire; et /ou pontage coronaire.
Les artérioles rétiniennes des sujets ATH ont montré un rétrécissement significatif par rapport aux sujets témoins. En outre, une différence significative entre les mesures de textures d'images prises sur les artérioles et les veinules rétiniennes et leurs régions adjacentes a été trouvée entre les sujets ATH et les sujets témoins.
Nos Ă©tudes transversales ont montrĂ© que lâanalyse hyperspectrale des images rĂ©tiniennes pouvait discerner avec une prĂ©cision acceptable lâAD et lâATH des sujets tĂ©moins correspondants.----------ABSTRACT
The fact that eye can be visualized non-invasively, opens up possibilities to measure biomarkers for diagnosis of long-term conditions. A significant body of literature has demonstrated that many of the neurodegenerative and cardiovascular diseases such as Alzheimerâs disease (AD) and atherosclerosis (ATH) manifest themselves in retina as pathological and/or vasculature morphological changes. Methods for two-dimensional fundus imaging and techniques for three-dimensional optical coherence tomography (OCT) have been developed to provide descriptions of retinal structures. However, images acquired by these techniques mostly allow for measuring the spatial characteristics of the tissue and lack of the relative variances across differing wavelengths, thus important spectral features may remain uncovered.
In this study, a Metabolic Hyperspectral Retinal Camera (MHRC) was used that permits the acquisition of a series of retinal images obtained at specific wavelengths covering the visible and near infrared (NIR) spectrum. In this technique, light transmittance, absorption, and scatter are reflected in the spectrum of light emitted from the tissue. Use of MHRC in this study was aimed to extract not only the common spatial features but also âspectral signaturesâ of biomolecules in retinal tissue.
Regarding the costs and limitations of the current diagnostic methods for AD and ATH, the purpose of this thesis was to analyze the information content of data-rich hyperspectral retinal images to characterize tissue-related discriminatory information to identify possible biomarkers of Alzheimerâs disease and atherosclerosis. To this end, a combination of vascular features and spatial/spectral texture measures were extracted from different anatomical regions of the retina.
In the context of AD, retinal images from 20 cognitively impaired and 26 cognitively unimpaired cases were acquired using MHRC. The cerebral amyloid status was determined from binary reads by a panel of three expert raters on 18F-Florbetaben PET studies. Our approach did not aim to visualize directly AÎČ deposits in the retina but rather to determine a likely amyloid status based on sets of retinal image features highly correlated with the cerebral amyloid status.
Retinal image features were calculated including vesselsâ tortuosity and diameter. Spatial/spectral texture measures over arterioles, venules, and tissue around were also extracted. Retinal venules of amyloid positive subjects (AÎČ+) showed a higher mean tortuosity compared to the amyloid negative (AÎČ-) subjects. Arteriolar diameter of AÎČ+ subjects was found to be higher than the AÎČ- subjects in a zone adjacent to the optical nerve head. Furthermore, a significant difference between spatial/spectral texture measures built over retinal arterioles and surrounding tissues were observed in AÎČ+ subjects when compared to the AÎČ-.
In the context of ATH, 60 retinal images from 30 clinically probable ATH and 30 control cases were acquired. Inclusion criteria for subjects suffering from ATH included: myocardial infarction; coronary angiography showing at least one coronary stenosis (more than 50%); and/or coronary angioplasty; and/or coronary bypass.
Retinal arterioles of ATH subjects showed a significant narrowing when compared to control subjects. Moreover, a significant difference between image texture measures taken over retinal arterioles and retinal venules and their adjacent regions was observed between ATH subjects and control subjects.
Our cross-sectional studies have shown that hyperspectral retinal image analysis could be used to discriminate AD and ATH from corresponding control subjects based on a non-invasive eye scan
Visual field and structural alterations in age-related macular degeneration
The thesis investigated progression of the central 10° visual field with structural changes at the macula in a cross-section of patients with varying degrees of agerelated macular degeneration (AMD). The relationships between structure and function were investigated for both standard and short-wavelength automated perimetry (SWAP). Factors known to influence the measure of visual field progression were considered, including the accuracy of the refractive correction on SWAP thresholds and the learning effect. Techniques of assessing the structure to function relationships between fundus images and the visual field were developed with computer programming and evaluated for repeatability. Drusen quantification of fundus photographs and retro-mode scanning laser ophthalmoscopic images was performed. Visual field progression was related to structural changes derived from both manual and automated methods. Principal Findings: ⹠Visual field sensitivity declined with advancing stage of AMD. SWAP showed greater sensitivity to progressive changes than standard perimetry. ⹠Defects were confined to the central 5°. SWAP defects occurred at similar locations but were deeper and wider than corresponding standard perimetry defects. ⹠The central field became less uniform as severity of AMD increased. SWAP visual field indices of focal loss were of more importance when detecting early change in AMD, than indices of diffuse loss. ⹠The decline in visual field sensitivity over stage of severity of AMD was not uniform, whereas a linear relationship was found between the automated measure of drusen area and visual field parameters. ⹠Perimetry exhibited a stronger relationship with drusen area than other measures of visual function. ⹠Overcorrection of the refraction for the working distance in SWAP should be avoided in subjects with insufficient accommodative facility. ⹠The perimetric learning effect in the 10° field did not differ significantly between normal subjects and AMD patients. ⹠Subretinal deposits appeared more numerous in retro-mode imaging than in fundus photography
Quantitative Binocular Assessment Using Infrared Video Photoscreening
Photorefraction is a technique that has been used in the past two decades for pediatric vision screening. The technique uses a digital or photographic camera to capture the examineeâs retinal reflex from a light source that is located near the cameraâs lens. It has the advantages of being objective, binocular and low cost, which make it a good candidate for pediatric screening when compared to other methods. Although many children have been screened using this technique in the U.S., its sensitivity and other disadvantages make it unacceptable for continued use. The Adaptive Photorefraction system (APS) was developed at the Center for Laser Applications (CLA) at the University of Tennessee Space Institute (UTSI) to correct the problems in the existing PS devices. APS was designed to determine quantitatively binocular refractive errors and strabismus and to accomplish these tasks objectively, without the need of medical professionals, and it is capable of performing these objectives and reporting the digitally recorded results within one- to-two minutes.
In this dissertation, two APS prototypes were constructed, and measurements were performed using both an artificial eye and human subjects. Binocular measurements of refractive error were determined, and the effects of the variation of pupil-size and gaze angle were determined. After initial corrections for ocular scattering effects, measurement of the binocular refractive error of forty human subjects was achieved, and in the myopic region with uncertainty of the method was 0.6 diopter. Ocular alignment determinations were achieved, and using a novel cover-uncover test, strabismus detection was demonstrated
Vessel identification in diabetic retinopathy
Diabetic retinopathy is the single largest cause of sight loss and blindness in 18 to 65 year olds. Screening programs for the estimated one to six per- cent of the diabetic population have been demonstrated to be cost and sight saving, howeverthere are insufficient screening resources. Automatic screen-ing systems may help solve this resource short fall. This thesis reports on research into an aspect of automatic grading of diabetic retinopathy; namely the identification of the retinal blood vessels in fundus photographs. It de-velops two vessels segmentation strategies and assess their accuracies. A literature review of retinal vascular segmentation found few results,
and indicated a need for further development. The two methods for vessel segmentation were investigated in this thesis are based on mathematical morphology and neural networks. Both methodologies are verified on independently labeled data from two institutions and results are presented that characterisethe trade off betweenthe ability to identify vesseland non-vessels data. These results are based on thirty five images with their retinal vessels
labeled. Of these images over half had significant pathology and or image acquisition artifacts. The morphological segmentation used ten images from one dataset for development. The remaining images of this dataset and the entire set of 20 images from the seconddataset were then used to prospectively verify generaliastion. For the neural approach, the imageswere pooled and 26 randomly chosenimageswere usedin training whilst 9 were reserved
for prospective validation. Assuming equal importance, or cost, for vessel and non-vessel classifications, the following results were obtained; using mathematical morphology 84% correct classification of vascular and non-vascular pixels was obtained in the first dataset. This increased to 89% correct for the second dataset. Using the pooled data the neural approach achieved 88% correct identification accuracy. The spread of accuracies observed varied. It was highest in the small initial dataset with 16 and 10 percent standard deviation in vascular and non-vascular cases respectively. The lowest variability was observed in the neural classification, with a standard deviation of 5% for both accuracies. The less tangible outcomes of the research raises the issueof the selection
and subsequent distribution of the patterns for neural network training. Unfortunately this indication would require further labeling of precisely those cases that were felt to be the most difficult. I.e. the small vessels and border conditions between pathology and the retina. The more concrete, evidence based conclusions,characterise both the neural and the morphological methods over a range of operating points. Many of these operating points are comparable to the few results presented in the literature. The advantage of the author's approach lies in the neural method's consistent as well as accurate vascular classification
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