Retinal Imaging Techniques for Diabetic Retinopathy Screening

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Goh, James Kang Hao; Cheung, Carol Y.; Sim, Shaun Sebastian; Tan, Pok Chien; Tan, Gavin Siew Wei; Wong, Tien Yin

2016-01-01

Due to the increasing prevalence of diabetes mellitus, demand for diabetic retinopathy (DR) screening platforms is steeply increasing. Early detection and treatment of DR are key public health interventions that can greatly reduce the likelihood of vision loss. Current DR screening programs typically employ retinal fundus photography, which relies on skilled readers for manual DR assessment. However, this is labor-intensive and suffers from inconsistency across sites. Hence, there has been a recent proliferation of automated retinal image analysis software that may potentially alleviate this burden cost-effectively. Furthermore, current screening programs based on 2-dimensional fundus photography do not effectively screen for diabetic macular edema (DME). Optical coherence tomography is becoming increasingly recognized as the reference standard for DME assessment and can potentially provide a cost-effective solution for improving DME detection in large-scale DR screening programs. Current screening techniques are also unable to image the peripheral retina and require pharmacological pupil dilation; ultra-widefield imaging and confocal scanning laser ophthalmoscopy, which address these drawbacks, possess great potential. In this review, we summarize the current DR screening methods using various retinal imaging techniques, and also outline future possibilities. Advances in retinal imaging techniques can potentially transform the management of patients with diabetes, providing savings in health care costs and resources. PMID:26830491

Detection of retinal nerve fiber layer defects in retinal fundus images using Gabor filtering

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Hayashi, Yoshinori; Nakagawa, Toshiaki; Hatanaka, Yuji; Aoyama, Akira; Kakogawa, Masakatsu; Hara, Takeshi; Fujita, Hiroshi; Yamamoto, Tetsuya

2007-03-01

Retinal nerve fiber layer defect (NFLD) is one of the most important findings for the diagnosis of glaucoma reported by ophthalmologists. However, such changes could be overlooked, especially in mass screenings, because ophthalmologists have limited time to search for a number of different changes for the diagnosis of various diseases such as diabetes, hypertension and glaucoma. Therefore, the use of a computer-aided detection (CAD) system can improve the results of diagnosis. In this work, a technique for the detection of NFLDs in retinal fundus images is proposed. In the preprocessing step, blood vessels are "erased" from the original retinal fundus image by using morphological filtering. The preprocessed image is then transformed into a rectangular array. NFLD regions are observed as vertical dark bands in the transformed image. Gabor filtering is then applied to enhance the vertical dark bands. False positives (FPs) are reduced by a rule-based method which uses the information of the location and the width of each candidate region. The detected regions are back-transformed into the original configuration. In this preliminary study, 71% of NFLD regions are detected with average number of FPs of 3.2 per image. In conclusion, we have developed a technique for the detection of NFLDs in retinal fundus images. Promising results have been obtained in this initial study.

In vivo fluorescence imaging of primate retinal ganglion cells and retinal pigment epithelial cells

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Gray, Daniel C.; Merigan, William; Wolfing, Jessica I.; Gee, Bernard P.; Porter, Jason; Dubra, Alfredo; Twietmeyer, Ted H.; Ahamd, Kamran; Tumbar, Remy; Reinholz, Fred; Williams, David R.

2006-08-01

The ability to resolve single cells noninvasively in the living retina has important applications for the study of normal retina, diseased retina, and the efficacy of therapies for retinal disease. We describe a new instrument for high-resolution, in vivo imaging of the mammalian retina that combines the benefits of confocal detection, adaptive optics, multispectral, and fluorescence imaging. The instrument is capable of imaging single ganglion cells and their axons through retrograde transport in ganglion cells of fluorescent dyes injected into the monkey lateral geniculate nucleus (LGN). In addition, we demonstrate a method involving simultaneous imaging in two spectral bands that allows the integration of very weak signals across many frames despite inter-frame movement of the eye. With this method, we are also able to resolve the smallest retinal capillaries in fluorescein angiography and the mosaic of retinal pigment epithelium (RPE) cells with lipofuscin autofluorescence.

Wide-field optical coherence tomography based microangiography for retinal imaging

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Zhang, Qinqin; Lee, Cecilia S.; Chao, Jennifer; Chen, Chieh-Li; Zhang, Thomas; Sharma, Utkarsh; Zhang, Anqi; Liu, Jin; Rezaei, Kasra; Pepple, Kathryn L.; Munsen, Richard; Kinyoun, James; Johnstone, Murray; van Gelder, Russell N.; Wang, Ruikang K.

2016-02-01

Optical coherence tomography angiography (OCTA) allows for the evaluation of functional retinal vascular networks without a need for contrast dyes. For sophisticated monitoring and diagnosis of retinal diseases, OCTA capable of providing wide-field and high definition images of retinal vasculature in a single image is desirable. We report OCTA with motion tracking through an auxiliary real-time line scan ophthalmoscope that is clinically feasible to image functional retinal vasculature in patients, with a coverage of more than 60 degrees of retina while still maintaining high definition and resolution. We demonstrate six illustrative cases with unprecedented details of vascular involvement in retinal diseases. In each case, OCTA yields images of the normal and diseased microvasculature at all levels of the retina, with higher resolution than observed with fluorescein angiography. Wide-field OCTA technology will be an important next step in augmenting the utility of OCT technology in clinical practice.

Fundus autofluorescence applications in retinal imaging

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Gabai, Andrea; Veritti, Daniele; Lanzetta, Paolo

2015-01-01

Fundus autofluorescence (FAF) is a relatively new imaging technique that can be used to study retinal diseases. It provides information on retinal metabolism and health. Several different pathologies can be detected. Peculiar AF alterations can help the clinician to monitor disease progression and to better understand its pathogenesis. In the present article, we review FAF principles and clinical applications. PMID:26139802

Fundus autofluorescence applications in retinal imaging

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Andrea Gabai

2015-01-01

Full Text Available Fundus autofluorescence (FAF is a relatively new imaging technique that can be used to study retinal diseases. It provides information on retinal metabolism and health. Several different pathologies can be detected. Peculiar AF alterations can help the clinician to monitor disease progression and to better understand its pathogenesis. In the present article, we review FAF principles and clinical applications.

Automatic detection and classification of malarial retinopathy- associated retinal whitening in digital retinal images

International Nuclear Information System (INIS)

Akram, M.U.; Alvi, A.B.N.; Khan, S.A.

2017-01-01

Malarial retinopathy addresses diseases that are characterized by abnormalities in retinal fundus imaging. Macular whitening is one of the distinct signs of cerebral malaria but has hardly been explored as a critical bio-marker. The paper proposes a computerized detection and classification method for malarial retinopathy using retinal whitening as a bio-marker. The paper combines various statistical and color based features to form a sound feature set for accurate detection of retinal whitening. All features are extracted at image level and feature selection is performed to detect most discriminate features. A new method for macula location is also presented. The detected macula location is further used for grading of whitening as macular or peripheral whitening. Support vector machine along with radial basis function is used for classification of normal and malarial retinopathy patients. The evaluation is performed using a locally gathered dataset from malarial patients and it achieves an accuracy of 95% for detection of retinal whitening and 100% accuracy for grading of retinal whitening as macular or non-macular. One of the major contributions of proposed method is grading of retinal whitening into macular or peripheral whitening. (author)

The relationship between the retinal image quality and the refractive index of defects arising in IOL: numerical analysis

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Geniusz, Malwina

2017-09-01

The best treatment for cataract patients, which allows to restore clear vision is implanting an artificial intraocular lens (IOL). The image quality of the lens has a significant impact on the quality of patient's vision. After a long exposure the implant to aqueous environment some defects appear in the artificial lenses. The defects generated in the IOL have different refractive indices. For example, glistening phenomenon is based on light scattering on the oval microvacuoles filled with an aqueous humor which refractive index value is about 1.34. Calcium deposits are another example of lens defects and they can be characterized by the refractive index 1.63. In the presented studies it was calculated how the difference between the refractive indices of the defect and the refractive index of the lens material affects the quality of image. The OpticStudio Professional program (from Radiant Zemax, LLC) was used for the construction of the numerical model of the eye with IOL and to calculate the characteristics of the retinal image. Retinal image quality was described in such characteristics as Point Spread Function (PSF) and the Optical Transfer Function with amplitude and phase. The results show a strong correlation between the refractive indices difference and retinal image quality.

High-speed adaptive optics line scan confocal retinal imaging for human eye.

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Lu, Jing; Gu, Boyu; Wang, Xiaolin; Zhang, Yuhua

2017-01-01

Continuous and rapid eye movement causes significant intraframe distortion in adaptive optics high resolution retinal imaging. To minimize this artifact, we developed a high speed adaptive optics line scan confocal retinal imaging system. A high speed line camera was employed to acquire retinal image and custom adaptive optics was developed to compensate the wave aberration of the human eye's optics. The spatial resolution and signal to noise ratio were assessed in model eye and in living human eye. The improvement of imaging fidelity was estimated by reduction of intra-frame distortion of retinal images acquired in the living human eyes with frame rates at 30 frames/second (FPS), 100 FPS, and 200 FPS. The device produced retinal image with cellular level resolution at 200 FPS with a digitization of 512×512 pixels/frame in the living human eye. Cone photoreceptors in the central fovea and rod photoreceptors near the fovea were resolved in three human subjects in normal chorioretinal health. Compared with retinal images acquired at 30 FPS, the intra-frame distortion in images taken at 200 FPS was reduced by 50.9% to 79.7%. We demonstrated the feasibility of acquiring high resolution retinal images in the living human eye at a speed that minimizes retinal motion artifact. This device may facilitate research involving subjects with nystagmus or unsteady fixation due to central vision loss.

Ultra-Widefield Steering-Based SD-OCT Imaging of the Retinal Periphery

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Choudhry, Netan; Golding, John; Manry, Matthew W.; Rao, Rajesh C.

2016-01-01

Objective To describe the spectral-domain optical coherence tomography (SD-OCT) features of peripheral retinal findings using an ultra-widefield (UWF) steering technique to image the retinal periphery. Design Observational study. Participants 68 patients (68 eyes) with 19 peripheral retinal features. Main Outcome Measures SD-OCT-based structural features. Methods Nineteen peripheral retinal features including: vortex vein, congenital hypertrophy of the retinal pigment epithelium (CHRPE), pars plana, ora serrata pearl, typical cystoid degeneration (TCD), cystic retinal tuft, meridional fold, lattice and cobblestone degeneration, retinal hole, retinal tear, rhegmatogenous retinal detachment (RRD), typical degenerative senile retinoschisis, peripheral laser coagulation scars, ora tooth, cryopexy scars (retinal tear and treated retinoblastoma scar), bone spicules, white without pressure, and peripheral drusen were identified by peripheral clinical examination. Near infrared (NIR) scanning laser ophthalmoscopy (SLO) images and SD-OCT of these entities were registered to UWF color photographs. Results SD-OCT resolved structural features of all peripheral findings. Dilated hyporeflective tubular structures within the choroid were observed in the vortex vein. Loss of retinal lamination, neural retinal attenuation, RPE loss or hypertrophy were seen in several entities including CHRPE, ora serrata pearl, TCD, cystic retinal tuft, meridional fold, lattice and cobblestone degenerations. Hyporeflective intraretinal spaces, indicating cystoid or schitic fluid, were seen in ora serrata pearl, ora tooth, TCD, cystic retinal tuft, meridional fold, retinal hole, and typical degenerative senile retinoschisis. The vitreoretinal interface, which often consisted of lamellae-like structures of the condensed cortical vitreous near or adherent to the neural retina, appeared clearly in most peripheral findings, confirming its association with many low-risk and vision-threatening pathologies

Image restoration, uncertainty, and information.

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Yu, F T

1969-01-01

Some of the physical interpretations about image restoration are discussed. From the theory of information the unrealizability of an inverse filter can be explained by degradation of information, which is due to distortion on the recorded image. The image restoration is a time and space problem, which can be recognized from the theory of relativity (the problem of image restoration is related to Heisenberg's uncertainty principle in quantum mechanics). A detailed discussion of the relationship between information and energy is given. Two general results may be stated: (1) the restoration of the image from the distorted signal is possible only if it satisfies the detectability condition. However, the restored image, at the best, can only approach to the maximum allowable time criterion. (2) The restoration of an image by superimposing the distorted signal (due to smearing) is a physically unrealizable method. However, this restoration procedure may be achieved by the expenditure of an infinite amount of energy.

EFFECTUAL HUMAN AUTHENTICATION FOR CRITICAL SECURITY APPLICATIONS USING RETINAL IMAGES

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L. Latha

2010-11-01

Full Text Available A robust method of human authentication based on the retinal blood vessel pattern is presented in this paper. This method entails a segmentation process to identify retinal blood vessel pattern, template generation consisting of the bifurcation points in the retina and matching of the intersection points in the template patterns. The number of matched blood vessel intersection points between the two patterns compared is used as a measure of similarity. As Liveness detection is a highly desirable anti-spoofing measure in biometric authentication, it is ensured while acquiring retinal images in realtime. The validity of our approach is verified with experimental results obtained from 603 comparisons made using 303 retinal images from three different publicly available databases, namely DRIVE, VARIA and STARE. We found that the proposed retinal recognition method gives 100%, 96.3% and 91.1% recognition rates respectively for the above databases. To the best of our knowledge, this is the first work that uses a large number of retinal images from different retinal databases for the authentication purpose.

Portable, low-priced retinal imager for eye disease screening

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Soliz, Peter; Nemeth, Sheila; VanNess, Richard; Barriga, E. S.; Zamora, Gilberto

2014-02-01

The objective of this project was to develop and demonstrate a portable, low-priced, easy to use non-mydriatic retinal camera for eye disease screening in underserved urban and rural locations. Existing portable retinal imagers do not meet the requirements of a low-cost camera with sufficient technical capabilities (field of view, image quality, portability, battery power, and ease-of-use) to be distributed widely to low volume clinics, such as the offices of single primary care physicians serving rural communities or other economically stressed healthcare facilities. Our approach for Smart i-Rx is based primarily on a significant departure from current generations of desktop and hand-held commercial retinal cameras as well as those under development. Our techniques include: 1) Exclusive use of off-the-shelf components; 2) Integration of retinal imaging device into low-cost, high utility camera mount and chin rest; 3) Unique optical and illumination designed for small form factor; and 4) Exploitation of autofocus technology built into present digital SLR recreational cameras; and 5) Integration of a polarization technique to avoid the corneal reflex. In a prospective study, 41 out of 44 diabetics were imaged successfully. No imaging was attempted on three of the subjects due to noticeably small pupils (less than 2mm). The images were of sufficient quality to detect abnormalities related to diabetic retinopathy, such as microaneurysms and exudates. These images were compared with ones taken non-mydriatically with a Canon CR-1 Mark II camera. No cases identified as having DR by expert retinal graders were missed in the Smart i-Rx images.

Histogram-Based Thresholding for Detection and Quantification of Hemorrhages in Retinal Images

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Hussain Fadhel Hamdan Jaafar

2016-12-01

Full Text Available Retinal image analysis is commonly used for the detection and quantification of retinal diabetic retinopathy. In retinal images, dark lesions including hemorrhages and microaneurysms are the earliest warnings of vision loss. In this paper, new algorithm for extraction and quantification of hemorrhages in fundus images is presented. Hemorrhage candidates are extracted in a preliminary step as a coarse segmentation followed by a fine segmentation step. Local variation processes are applied in the coarse segmentation step to determine boundaries of all candidates with distinct edges. Fine segmentation processes are based on histogram thresholding to extract real hemorrhages from the segmented candidates locally. The proposed method was trained and tested using an image dataset of 153 manually labeled retinal images. At the pixel level, the proposed method could identify abnormal retinal images with 90.7% sensitivity and 85.1% predictive value. Due to its distinctive performance measurements, this technique demonstrates that it could be used for a computer-aided mass screening of retinal diseases.

WIDEFIELD SPECTRAL-DOMAIN OPTICAL COHERENCE TOMOGRAPHY IMAGING OF PERIPHERAL ROUND RETINAL HOLES WITH OR WITHOUT RETINAL DETACHMENT.

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Casswell, Edward J; Abou Ltaif, Sleiman; Carr, Thomas; Keane, Pearse A; Charteris, David G; Wickham, Louisa

2018-03-02

To describe the widefield spectral-domain optical coherence tomography features of peripheral round retinal holes, with or without associated retinal detachment (RD). Retrospective, observational study of 28 eyes with peripheral round retinal holes, with and without RD. Patients underwent imaging with a widefield 50-degree spectral-domain optical coherence tomography (Heidelberg Engineering, Germany) and Optos ultra-widefield imaging systems (Optos, United Kingdom). Vitreous attachment at the site of the retinal hole was detected in 27/28 (96.4%) cases. Cases were split into three groups: RHs with RD (n = 12); RHs with subretinal fluid (n = 5), and flat RHs (n = 11), with minimal or no subretinal fluid. 91.6% retinal holes associated with subretinal fluid or RD had vitreous attachment at the site of the hole. Eighty percent had vitreous attachment at both edges of the retinal hole, in a U-shape configuration, which appeared to exert traction. By contrast, flat retinal holes had visible vitreous attachment only at one edge of the retinal hole in 45.4%. Vitreous attachment was commonly seen at the site of round retinal holes. Vitreous attachment at both edges of the retinal hole in a U-shape configuration was more commonly seen at holes associated with subretinal fluid or RD.

Tuberculoid leprosy and cytomegalovirus retinitis as immune restoration disease in a patient with AIDS.

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Kumar, Shishir; Ghosh, Manab Kumar; Sarkar, Somenath; Mallik, Sudeshna; Biswas, Pradyot Narayan; Saha, Bibhuti

2012-02-01

Here we report a unique case of tuberculoid leprosy and cytomegalovirus retinitis in a 27-year-old female patient with AIDS, suggestive of highly active antiretroviral therapy (HAART)-induced immune restoration disease. After initiation of HAART, the patient presented with decreased visual acuity, hypoesthetic patch with local nerve thickening, and an increase in her CD4+ T cell count. On further investigations cytomegalovirus retinitis and tuberculoid leprosy were confirmed. To our knowledge no case with such a co-existence has previously been reported. Copyright © 2011 International Society for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

User-guided segmentation for volumetric retinal optical coherence tomography images

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Yin, Xin; Chao, Jennifer R.; Wang, Ruikang K.

2014-01-01

Abstract. Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method. PMID:25147962

MR imaging findings of retinal hemorrhage in a case of nonaccidental trauma

International Nuclear Information System (INIS)

Altinok, Deniz; Saleem, Sheena; Smith, Wilbur; Zhang, Zaixiang; Markman, Lisa

2009-01-01

Retinal hemorrhage is a well-recognized manifestation of child abuse found in many babies with shaken baby syndrome. The presence of retinal hemorrhage is generally associated with more severe neurological damage and a worse clinical outcome. MR imaging findings of retinal hemorrhages are not well described in the pediatric literature. We present a 6-month-old boy with new-onset seizures, subdural hemorrhage and bilateral retinal hemorrhages that were detected by MRI and confirmed by indirect ophthalmoscopy. This case demonstrates the MR imaging findings of retinal hemorrhages and the importance of radiologists being able to recognize these specific imaging features. (orig.)

MR imaging findings of retinal hemorrhage in a case of nonaccidental trauma

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Altinok, Deniz; Saleem, Sheena; Smith, Wilbur [Children' s Hospital of Michigan, Department of Pediatric Imaging, Detroit, MI (United States); Zhang, Zaixiang [Wayne State University School of Medicine, Department of Radiology, Detroit, MI (United States); Markman, Lisa [Children' s Hospital of Michigan, Child Protection Team, Detroit, MI (United States)

2009-03-15

Retinal hemorrhage is a well-recognized manifestation of child abuse found in many babies with shaken baby syndrome. The presence of retinal hemorrhage is generally associated with more severe neurological damage and a worse clinical outcome. MR imaging findings of retinal hemorrhages are not well described in the pediatric literature. We present a 6-month-old boy with new-onset seizures, subdural hemorrhage and bilateral retinal hemorrhages that were detected by MRI and confirmed by indirect ophthalmoscopy. This case demonstrates the MR imaging findings of retinal hemorrhages and the importance of radiologists being able to recognize these specific imaging features. (orig.)

In Vivo Imaging of Retinal Hypoxia in a Model of Oxygen-Induced Retinopathy.

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Uddin, Md Imam; Evans, Stephanie M; Craft, Jason R; Capozzi, Megan E; McCollum, Gary W; Yang, Rong; Marnett, Lawrence J; Uddin, Md Jashim; Jayagopal, Ashwath; Penn, John S

2016-08-05

Ischemia-induced hypoxia elicits retinal neovascularization and is a major component of several blinding retinopathies such as retinopathy of prematurity (ROP), diabetic retinopathy (DR) and retinal vein occlusion (RVO). Currently, noninvasive imaging techniques capable of detecting and monitoring retinal hypoxia in living systems do not exist. Such techniques would greatly clarify the role of hypoxia in experimental and human retinal neovascular pathogenesis. In this study, we developed and characterized HYPOX-4, a fluorescence-imaging probe capable of detecting retinal-hypoxia in living animals. HYPOX-4 dependent in vivo and ex vivo imaging of hypoxia was tested in a mouse model of oxygen-induced retinopathy (OIR). Predicted patterns of retinal hypoxia were imaged by HYPOX-4 dependent fluorescence activity in this animal model. In retinal cells and mouse retinal tissue, pimonidazole-adduct immunostaining confirmed the hypoxia selectivity of HYPOX-4. HYPOX-4 had no effect on retinal cell proliferation as indicated by BrdU assay and exhibited no acute toxicity in retinal tissue as indicated by TUNEL assay and electroretinography (ERG) analysis. Therefore, HYPOX-4 could potentially serve as the basis for in vivo fluorescence-based hypoxia-imaging techniques, providing a tool for investigators to understand the pathogenesis of ischemic retinopathies and for physicians to address unmet clinical needs.

Objective and expert-independent validation of retinal image registration algorithms by a projective imaging distortion model.

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Lee, Sangyeol; Reinhardt, Joseph M; Cattin, Philippe C; Abràmoff, Michael D

2010-08-01

Fundus camera imaging of the retina is widely used to diagnose and manage ophthalmologic disorders including diabetic retinopathy, glaucoma, and age-related macular degeneration. Retinal images typically have a limited field of view, and multiple images can be joined together using an image registration technique to form a montage with a larger field of view. A variety of methods for retinal image registration have been proposed, but evaluating such methods objectively is difficult due to the lack of a reference standard for the true alignment of the individual images that make up the montage. A method of generating simulated retinal images by modeling the geometric distortions due to the eye geometry and the image acquisition process is described in this paper. We also present a validation process that can be used for any retinal image registration method by tracing through the distortion path and assessing the geometric misalignment in the coordinate system of the reference standard. The proposed method can be used to perform an accuracy evaluation over the whole image, so that distortion in the non-overlapping regions of the montage components can be easily assessed. We demonstrate the technique by generating test image sets with a variety of overlap conditions and compare the accuracy of several retinal image registration models. Copyright 2010 Elsevier B.V. All rights reserved.

Noninvasive Quantification of Retinal Microglia Using Widefield Autofluorescence Imaging.

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Kokona, Despina; Schneider, Nadia; Giannakaki-Zimmermann, Helena; Jovanovic, Joel; Ebneter, Andreas; Zinkernagel, Martin

2017-04-01

To validate widefield autofluorescence (AF) in vivo imaging of the retina in mice expressing green fluorescent protein (gfp) in microglia, and to monitor retinal microglia reconstitution in vivo after lethal irradiation and bone marrow transplantation. Transgenic Cx3cr1gfp/gfp and wildtype Balb/c mice were used in this study. A confocal scanning laser ophthalmoscope was used for AF imaging with a 55° and a widefield 102° lens. Intrasession reproducibility was assessed for each lens. To investigate reconstitution in vivo, bone marrow from Cx3cr1gfp/gfp mice was used to rescue lethally irradiated wildtype mice. Data were compared to confocal microscopy of retinal flat mounts. Both the 55° and the 102° lens produced high resolution images of retinal microglia with similar microglia density. However, compared to the 55° lens, the widefield 102° lens captured approximately 3.6 times more microglia cells (1515 ± 123 cells versus 445 ± 76 cells [mean ± SD], for 102° and 55°, respectively, P < 0.001). No statistical difference in the number of gfp positive cells within corresponding areas was observed within the same imaging session. Imaging of microglia reconstitution showed a similar time course compared to flat mount preparations with an excellent correlation between microglia cell numbers in AF and gfp-stained flat mounts (R = 0.92, P < 0.0001). Widefield AF imaging of mice with gfp expressing microglia can be used to quantify retinal microglia. In vivo microglia counts corresponded very well with ex vivo counts on retinal flat mounts. As such, AF imaging can largely replace ex vivo quantification.

Enface Thickness Mapping and Reflectance Imaging of Retinal Layers in Diabetic Retinopathy.

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Francis, Andrew W; Wanek, Justin; Lim, Jennifer I; Shahidi, Mahnaz

2015-01-01

To present a method for image segmentation and generation of enface thickness maps and reflectance images of retinal layers in healthy and diabetic retinopathy (DR) subjects. High density spectral domain optical coherence tomography (SDOCT) images were acquired in 10 healthy and 4 DR subjects. Customized image analysis software identified 5 retinal cell layer interfaces and generated thickness maps and reflectance images of the total retina (TR), inner retina (IR), outer retina (OR), and the inner segment ellipsoid (ISe) band. Thickness maps in DR subjects were compared to those of healthy subjects by generating deviation maps which displayed retinal locations with thickness below, within, and above the normal 95% confidence interval. In healthy subjects, TR and IR thickness maps displayed the foveal depression and increased thickness in the parafoveal region. OR and ISe thickness maps showed increased thickness at the fovea, consistent with normal retinal anatomy. In DR subjects, thickening and thinning in localized regions were demonstrated on TR, IR, OR, and ISe thickness maps, corresponding to retinal edema and atrophy, respectively. TR and OR reflectance images showed reduced reflectivity in regions of increased thickness. Hard exudates appeared as hyper-reflective spots in IR reflectance images and casted shadows on the deeper OR and ISe reflectance images. The ISe reflectance image clearly showed the presence of focal laser scars. Enface thickness mapping and reflectance imaging of retinal layers is a potentially useful method for quantifying the spatial and axial extent of pathologies due to DR.

Toward high-resolution optoelectronic retinal prosthesis

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Palanker, Daniel; Huie, Philip; Vankov, Alexander; Asher, Alon; Baccus, Steven

2005-04-01

It has been already demonstrated that electrical stimulation of retina can produce visual percepts in blind patients suffering from macular degeneration and retinitis pigmentosa. Current retinal implants provide very low resolution (just a few electrodes), while several thousand pixels are required for functional restoration of sight. We present a design of the optoelectronic retinal prosthetic system that can activate a retinal stimulating array with pixel density up to 2,500 pix/mm2 (geometrically corresponding to a visual acuity of 20/80), and allows for natural eye scanning rather than scanning with a head-mounted camera. The system operates similarly to "virtual reality" imaging devices used in military and medical applications. An image from a video camera is projected by a goggle-mounted infrared LED-LCD display onto the retina, activating an array of powered photodiodes in the retinal implant. Such a system provides a broad field of vision by allowing for natural eye scanning. The goggles are transparent to visible light, thus allowing for simultaneous utilization of remaining natural vision along with prosthetic stimulation. Optical control of the implant allows for simple adjustment of image processing algorithms and for learning. A major prerequisite for high resolution stimulation is the proximity of neural cells to the stimulation sites. This can be achieved with sub-retinal implants constructed in a manner that directs migration of retinal cells to target areas. Two basic implant geometries are described: perforated membranes and protruding electrode arrays. Possibility of the tactile neural stimulation is also examined.

Screening retinal transplants with Fourier-domain OCT

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Rao, Bin

2009-02-01

Transplant technologies have been studied for the recovery of vision loss from retinitis pigmentosa (RP) and age-related macular degeneration (AMD). In several rodent retinal degeneration models and in patients, retinal progenitor cells transplanted as layers to the subretinal space have been shown to restore or preserve vision. The methods for evaluation of transplants are expensive considering the large amount of animals. Alternatively, time-domain Stratus OCT was previously shown to be able to image the morphological structure of transplants to some extent, but could not clearly identify laminated transplants. The efficacy of screening retinal transplants with Fourier-domain OCT was studied on 37 S334ter line 3 rats with retinal degeneration 6-67 days after transplant surgery. The transplants were morphologically categorized as no transplant, detachment, rosettes, small laminated area and larger laminated area with both Fourier-domain OCT and histology. The efficacy of Fourier-domain OCT in screening retinal transplants was evaluated by comparing the categorization results with OCT and histology. Additionally, 4 rats were randomly selected for multiple OCT examinations (1, 5, 9, 14 and 21days post surgery) in order to determine the earliest image time of OCT examination since the transplanted tissue may need some time to show its tendency of growing. Finally, we demonstrated the efficacy of Fourier-domain OCT in screening retinal transplants in early stages and determined the earliest imaging time for OCT. Fourier-domain OCT makes itself valuable in saving resource spent on animals with unsuccessful transplants.

Ectopic norrin induces growth of ocular capillaries and restores normal retinal angiogenesis in Norrie disease mutant mice.

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Ohlmann, Andreas; Scholz, Michael; Goldwich, Andreas; Chauhan, Bharesh K; Hudl, Kristiane; Ohlmann, Anne V; Zrenner, Eberhart; Berger, Wolfgang; Cvekl, Ales; Seeliger, Mathias W; Tamm, Ernst R

2005-02-16

Norrie disease is an X-linked retinal dysplasia that presents with congenital blindness, sensorineural deafness, and mental retardation. Norrin, the protein product of the Norrie disease gene (NDP), is a secreted protein of unknown biochemical function. Norrie disease (Ndp(y/-)) mutant mice that are deficient in norrin develop blindness, show a distinct failure in retinal angiogenesis, and completely lack the deep capillary layers of the retina. We show here that the transgenic expression of ectopic norrin under control of a lens-specific promoter restores the formation of a normal retinal vascular network in Ndp(y/-) mutant mice. The improvement in structure correlates with restoration of neuronal function in the retina. In addition, lenses of transgenic mice with ectopic expression of norrin show significantly more capillaries in the hyaloid vasculature that surrounds the lens during development. In vitro, lenses of transgenic mice in coculture with microvascular endothelial cells induce proliferation of the cells. Transgenic mice with ectopic expression of norrin show more bromodeoxyuridine-labeled retinal progenitor cells at embryonic day 14.5 and thicker retinas at postnatal life than wild-type littermates, indicating a putative direct neurotrophic effect of norrin. These data provide direct evidence that norrin induces growth of ocular capillaries and that pharmacologic modulation of norrin might be used for treatment of the vascular abnormalities associated with Norrie disease or other vascular disorders of the retina.

Multiple evanescent white dot syndrome associated with retinal vasculitis

Directory of Open Access Journals (Sweden)

Takahashi A

2015-09-01

Full Text Available Akihiro Takahashi, Wataru Saito, Yuki Hashimoto, Susumu Ishida Department of Ophthalmology, Hokkaido University Graduate School of Medicine, Sapporo, Japan Purpose: A recent study revealed thickening of the inner retinal layers in acute stage of multiple evanescent white dot syndrome (MEWDS; however, the pathogenesis is still unknown. We report two cases with MEWDS whose funduscopy showed obvious retinal vasculitis. Methods: Case reports. Results: Healthy myopic 16- and 27-year-old women were the cases under study. In both cases, funduscopic examination revealed multiple, faint, small, subretinal white dots at the posterior pole to the midperiphery and macular granularity oculus dexter. Retinal vascular sheathing was also observed at midperiphery. Late-phase fluorescein angiography revealed leakages corresponding to the vascular sheathing. Enhanced depth imaging optical coherence tomography revealed the discontinuity of the ellipsoid zone corresponding to the white dots and increased macular choroidal thickness. One month later, these white dots and retinal sheathing spontaneously resolved in both cases. Three months later, impairments of the outer retinal morphology and the visual acuity were restored. Conclusion: These results suggest that retinal vasculitis possibly plays a role in the pathogenesis of thickened inner retinal layers in acute stage of MEWDS. Keywords: enhanced depth imaging optical coherence tomography, choroidal thickness, inner retinal layer, retinal vascular sheathing

In vivo imaging of the retinal pigment epithelial cells

Science.gov (United States)

Morgan, Jessica Ijams Wolfing

The retinal pigment epithelial (RPE) cells form an important layer of the retina because they are responsible for providing metabolic support to the photoreceptors. Techniques to image the RPE layer include autofluorescence imaging with a scanning laser ophthalmoscope (SLO). However, previous studies were unable to resolve single RPE cells in vivo. This thesis describes the technique of combining autofluorescence, SLO, adaptive optics (AO), and dual-wavelength simultaneous imaging and registration to visualize the individual cells in the RPE mosaic in human and primate retina for the first time in vivo. After imaging the RPE mosaic non-invasively, the cell layer's structure and regularity were characterized using quantitative metrics of cell density, spacing, and nearest neighbor distances. The RPE mosaic was compared to the cone mosaic, and RPE imaging methods were confirmed using histology. The ability to image the RPE mosaic led to the discovery of a novel retinal change following light exposure; 568 nm exposures caused an immediate reduction in autofluorescence followed by either full recovery or permanent damage in the RPE layer. A safety study was conducted to determine the range of exposure irradiances that caused permanent damage or transient autofluorescence reductions. Additionally, the threshold exposure causing autofluorescence reduction was determined and reciprocity of radiant exposure was confirmed. Light exposures delivered by the AOSLO were not significantly different than those delivered by a uniform source. As all exposures tested were near or below the permissible light levels of safety standards, this thesis provides evidence that the current light safety standards need to be revised. Finally, with the retinal damage and autofluorescence reduction thresholds identified, the methods of RPE imaging were modified to allow successful imaging of the individual cells in the RPE mosaic while still ensuring retinal safety. This thesis has provided a

Restoration of motion blurred images

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Gaxiola, Leopoldo N.; Juarez-Salazar, Rigoberto; Diaz-Ramirez, Victor H.

2017-08-01

Image restoration is a classic problem in image processing. Image degradations can occur due to several reasons, for instance, imperfections of imaging systems, quantization errors, atmospheric turbulence, relative motion between camera or objects, among others. Motion blur is a typical degradation in dynamic imaging systems. In this work, we present a method to estimate the parameters of linear motion blur degradation from a captured blurred image. The proposed method is based on analyzing the frequency spectrum of a captured image in order to firstly estimate the degradation parameters, and then, to restore the image with a linear filter. The performance of the proposed method is evaluated by processing synthetic and real-life images. The obtained results are characterized in terms of accuracy of image restoration given by an objective criterion.

Lentiviral expression of retinal guanylate cyclase-1 (RetGC1 restores vision in an avian model of childhood blindness.

Directory of Open Access Journals (Sweden)

Melissa L Williams

2006-06-01

Full Text Available Leber congenital amaurosis (LCA is a genetically heterogeneous group of retinal diseases that cause congenital blindness in infants and children. Mutations in the GUCY2D gene that encodes retinal guanylate cyclase-1 (retGC1 were the first to be linked to this disease group (LCA type 1 [LCA1] and account for 10%-20% of LCA cases. These mutations disrupt synthesis of cGMP in photoreceptor cells, a key second messenger required for function of these cells. The GUCY1*B chicken, which carries a null mutation in the retGC1 gene, is blind at hatching and serves as an animal model for the study of LCA1 pathology and potential treatments in humans.A lentivirus-based gene transfer vector carrying the GUCY2D gene was developed and injected into early-stage GUCY1*B embryos to determine if photoreceptor function and sight could be restored to these animals. Like human LCA1, the avian disease shows early-onset blindness, but there is a window of opportunity for intervention. In both diseases there is a period of photoreceptor cell dysfunction that precedes retinal degeneration. Of seven treated animals, six exhibited sight as evidenced by robust optokinetic and volitional visual behaviors. Electroretinographic responses, absent in untreated animals, were partially restored in treated animals. Morphological analyses indicated there was slowing of the retinal degeneration.Blindness associated with loss of function of retGC1 in the GUCY1*B avian model of LCA1 can be reversed using viral vector-mediated gene transfer. Furthermore, this reversal can be achieved by restoring function to a relatively low percentage of retinal photoreceptors. These results represent a first step toward development of gene therapies for one of the more common forms of childhood blindness.

Live-cell imaging: new avenues to investigate retinal regeneration

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Manuela Lahne

2017-01-01

Full Text Available Sensing and responding to our environment requires functional neurons that act in concert. Neuronal cell loss resulting from degenerative diseases cannot be replaced in humans, causing a functional impairment to integrate and/or respond to sensory cues. In contrast, zebrafish (Danio rerio possess an endogenous capacity to regenerate lost neurons. Here, we will focus on the processes that lead to neuronal regeneration in the zebrafish retina. Dying retinal neurons release a damage signal, tumor necrosis factor α, which induces the resident radial glia, the Müller glia, to reprogram and re-enter the cell cycle. The Müller glia divide asymmetrically to produce a Müller glia that exits the cell cycle and a neuronal progenitor cell. The arising neuronal progenitor cells undergo several rounds of cell divisions before they migrate to the site of damage to differentiate into the neuronal cell types that were lost. Molecular and immunohistochemical studies have predominantly provided insight into the mechanisms that regulate retinal regeneration. However, many processes during retinal regeneration are dynamic and require live-cell imaging to fully discern the underlying mechanisms. Recently, a multiphoton imaging approach of adult zebrafish retinal cultures was developed. We will discuss the use of live-cell imaging, the currently available tools and those that need to be developed to advance our knowledge on major open questions in the field of retinal regeneration.

Ultra-Widefield Steering-Based Spectral-Domain Optical Coherence Tomography Imaging of the Retinal Periphery.

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Choudhry, Netan; Golding, John; Manry, Matthew W; Rao, Rajesh C

2016-06-01

To describe the spectral-domain optical coherence tomography (SD OCT) features of peripheral retinal findings using an ultra-widefield (UWF) steering technique to image the retinal periphery. Observational study. A total of 68 patients (68 eyes) with 19 peripheral retinal features. Spectral-domain OCT-based structural features. Nineteen peripheral retinal features, including vortex vein, congenital hypertrophy of the retinal pigment epithelium, pars plana, ora serrata pearl, typical cystoid degeneration (TCD), cystic retinal tuft, meridional fold, lattice and cobblestone degeneration, retinal hole, retinal tear, rhegmatogenous retinal detachment, typical degenerative senile retinoschisis, peripheral laser coagulation scars, ora tooth, cryopexy scars (retinal tear and treated retinoblastoma scar), bone spicules, white without pressure, and peripheral drusen, were identified by peripheral clinical examination. Near-infrared scanning laser ophthalmoscopy images and SD OCT of these entities were registered to UWF color photographs. Spectral-domain OCT resolved structural features of all peripheral findings. Dilated hyporeflective tubular structures within the choroid were observed in the vortex vein. Loss of retinal lamination, neural retinal attenuation, retinal pigment epithelium loss, or hypertrophy was seen in several entities, including congenital hypertrophy of the retinal pigment epithelium, ora serrata pearl, TCD, cystic retinal tuft, meridional fold, lattice, and cobblestone degenerations. Hyporeflective intraretinal spaces, indicating cystoid or schitic fluid, were seen in ora serrata pearl, ora tooth, TCD, cystic retinal tuft, meridional fold, retinal hole, and typical degenerative senile retinoschisis. The vitreoretinal interface, which often consisted of lamellae-like structures of the condensed cortical vitreous near or adherent to the neural retina, appeared clearly in most peripheral findings, confirming its association with many low-risk and vision

Design of a high-resolution optoelectronic retinal prosthesis.

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Palanker, Daniel; Vankov, Alexander; Huie, Phil; Baccus, Stephen

2005-03-01

It has been demonstrated that electrical stimulation of the retina can produce visual percepts in blind patients suffering from macular degeneration and retinitis pigmentosa. However, current retinal implants provide very low resolution (just a few electrodes), whereas at least several thousand pixels would be required for functional restoration of sight. This paper presents the design of an optoelectronic retinal prosthetic system with a stimulating pixel density of up to 2500 pix mm(-2) (corresponding geometrically to a maximum visual acuity of 20/80). Requirements on proximity of neural cells to the stimulation electrodes are described as a function of the desired resolution. Two basic geometries of sub-retinal implants providing required proximity are presented: perforated membranes and protruding electrode arrays. To provide for natural eye scanning of the scene, rather than scanning with a head-mounted camera, the system operates similar to 'virtual reality' devices. An image from a video camera is projected by a goggle-mounted collimated infrared LED-LCD display onto the retina, activating an array of powered photodiodes in the retinal implant. The goggles are transparent to visible light, thus allowing for the simultaneous use of remaining natural vision along with prosthetic stimulation. Optical delivery of visual information to the implant allows for real-time image processing adjustable to retinal architecture, as well as flexible control of image processing algorithms and stimulation parameters.

Design of a high-resolution optoelectronic retinal prosthesis

Science.gov (United States)

Palanker, Daniel; Vankov, Alexander; Huie, Phil; Baccus, Stephen

2005-03-01

It has been demonstrated that electrical stimulation of the retina can produce visual percepts in blind patients suffering from macular degeneration and retinitis pigmentosa. However, current retinal implants provide very low resolution (just a few electrodes), whereas at least several thousand pixels would be required for functional restoration of sight. This paper presents the design of an optoelectronic retinal prosthetic system with a stimulating pixel density of up to 2500 pix mm-2 (corresponding geometrically to a maximum visual acuity of 20/80). Requirements on proximity of neural cells to the stimulation electrodes are described as a function of the desired resolution. Two basic geometries of sub-retinal implants providing required proximity are presented: perforated membranes and protruding electrode arrays. To provide for natural eye scanning of the scene, rather than scanning with a head-mounted camera, the system operates similar to 'virtual reality' devices. An image from a video camera is projected by a goggle-mounted collimated infrared LED-LCD display onto the retina, activating an array of powered photodiodes in the retinal implant. The goggles are transparent to visible light, thus allowing for the simultaneous use of remaining natural vision along with prosthetic stimulation. Optical delivery of visual information to the implant allows for real-time image processing adjustable to retinal architecture, as well as flexible control of image processing algorithms and stimulation parameters.

Automatic segmentation of blood vessels from retinal fundus images ...

Indian Academy of Sciences (India)

The retinal blood vessels were segmented through color space conversion and color channel .... Retinal blood vessel segmentation was also attempted through multi-scale operators. A few works in this ... fundus camera at 35 degrees field of view. The image ... vessel segmentation is available from two human observers.

Adaptive optics imaging of inherited retinal diseases.

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Georgiou, Michalis; Kalitzeos, Angelos; Patterson, Emily J; Dubra, Alfredo; Carroll, Joseph; Michaelides, Michel

2017-11-15

Adaptive optics (AO) ophthalmoscopy allows for non-invasive retinal phenotyping on a microscopic scale, thereby helping to improve our understanding of retinal diseases. An increasing number of natural history studies and ongoing/planned interventional clinical trials exploit AO ophthalmoscopy both for participant selection, stratification and monitoring treatment safety and efficacy. In this review, we briefly discuss the evolution of AO ophthalmoscopy, recent developments and its application to a broad range of inherited retinal diseases, including Stargardt disease, retinitis pigmentosa and achromatopsia. Finally, we describe the impact of this in vivo microscopic imaging on our understanding of disease pathogenesis, clinical trial design and outcome metrics, while recognising the limitation of the small cohorts reported to date. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

ROV Based Underwater Blurred Image Restoration

Institute of Scientific and Technical Information of China (English)

LIU Zhishen; DING Tianfu; WANG Gang

2003-01-01

In this paper, we present a method of ROV based image processing to restore underwater blurry images from the theory of light and image transmission in the sea. Computer is used to simulate the maximum detection range of the ROV under different water body conditions. The receiving irradiance of the video camera at different detection ranges is also calculated. The ROV's detection performance under different water body conditions is given by simulation. We restore the underwater blurry images using the Wiener filter based on the simulation. The Wiener filter is shown to be a simple useful method for underwater image restoration in the ROV underwater experiments. We also present examples of restored images of an underwater standard target taken by the video camera in these experiments.

Prosthetic vision: devices, patient outcomes and retinal research.

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Hadjinicolaou, Alex E; Meffin, Hamish; Maturana, Matias I; Cloherty, Shaun L; Ibbotson, Michael R

2015-09-01

Retinal disease and its associated retinal degeneration can lead to the loss of photoreceptors and therefore, profound blindness. While retinal degeneration destroys the photoreceptors, the neural circuits that convey information from the eye to the brain are sufficiently preserved to make it possible to restore sight using prosthetic devices. Typically, these devices consist of a digital camera and an implantable neurostimulator. The image sensor in a digital camera has the same spatiotopic arrangement as the photoreceptors of the retina. Therefore, it is possible to extract meaningful spatial information from an image and deliver it via an array of stimulating electrodes directly to the surviving retinal circuits. Here, we review the structure and function of normal and degenerate retina. The different approaches to prosthetic implant design are described in the context of human and preclinical trials. In the last section, we review studies of electrical properties of the retina and its response to electrical stimulation. These types of investigation are currently assessing a number of key challenges identified in human trials, including stimulation efficacy, spatial localisation, desensitisation to repetitive stimulation and selective activation of retinal cell populations. © 2015 The Authors. Clinical and Experimental Optometry © 2015 Optometry Australia.

STUDY OF IMAGE SEGMENTATION TECHNIQUES ON RETINAL IMAGES FOR HEALTH CARE MANAGEMENT WITH FAST COMPUTING

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Srikanth Prabhu

2012-02-01

Full Text Available The role of segmentation in image processing is to separate foreground from background. In this process, the features become clearly visible when appropriate filters are applied on the image. In this paper emphasis has been laid on segmentation of biometric retinal images to filter out the vessels explicitly for evaluating the bifurcation points and features for diabetic retinopathy. Segmentation on images is performed by calculating ridges or morphology. Ridges are those areas in the images where there is sharp contrast in features. Morphology targets the features using structuring elements. Structuring elements are of different shapes like disk, line which is used for extracting features of those shapes. When segmentation was performed on retinal images problems were encountered during image pre-processing stage. Also edge detection techniques have been deployed to find out the contours of the retinal images. After the segmentation has been performed, it has been seen that artifacts of the retinal images have been minimal when ridge based segmentation technique was deployed. In the field of Health Care Management, image segmentation has an important role to play as it determines whether a person is normal or having any disease specially diabetes. During the process of segmentation, diseased features are classified as diseased one’s or artifacts. The problem comes when artifacts are classified as diseased ones. This results in misclassification which has been discussed in the analysis Section. We have achieved fast computing with better performance, in terms of speed for non-repeating features, when compared to repeating features.

Concurrent OCT imaging of stimulus evoked retinal neural activation and hemodynamic responses

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Son, Taeyoon; Wang, Benquan; Lu, Yiming; Chen, Yanjun; Cao, Dingcai; Yao, Xincheng

2017-02-01

It is well established that major retinal diseases involve distortions of the retinal neural physiology and blood vascular structures. However, the details of distortions in retinal neurovascular coupling associated with major eye diseases are not well understood. In this study, a multi-modal optical coherence tomography (OCT) imaging system was developed to enable concurrent imaging of retinal neural activity and vascular hemodynamics. Flicker light stimulation was applied to mouse retinas to evoke retinal neural responses and hemodynamic changes. The OCT images were acquired continuously during the pre-stimulation, light-stimulation, and post-stimulation phases. Stimulus-evoked intrinsic optical signals (IOSs) and hemodynamic changes were observed over time in blood-free and blood regions, respectively. Rapid IOSs change occurred almost immediately after stimulation. Both positive and negative signals were observed in adjacent retinal areas. The hemodynamic changes showed time delays after stimulation. The signal magnitudes induced by light stimulation were observed in blood regions and did not show significant changes in blood-free regions. These differences may arise from different mechanisms in blood vessels and neural tissues in response to light stimulation. These characteristics agreed well with our previous observations in mouse retinas. Further development of the multimodal OCT may provide a new imaging method for studying how retinal structures and metabolic and neural functions are affected by age-related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), and other diseases, which promises novel noninvasive biomarkers for early disease detection and reliable treatment evaluations of eye diseases.

In vivo sectional imaging of the retinal periphery using conventional optical coherence tomography systems

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Abhishek Kothari

2012-01-01

Full Text Available Optical coherence tomography (OCT has transformed macular disease practices. This report describes the use of conventional OCT systems for peripheral retinal imaging. Thirty-six eyes with peripheral retinal pathology underwent imaging with conventional OCT systems. In vivo sectional imaging of lattice degeneration, snail-track degeneration, and paving-stone degeneration was performed. Differences were noted between phenotypes of lattice degeneration. Several findings previously unreported in histopathology studies were encountered. Certain anatomic features were seen that could conceivably explain clinical and intraoperative behavior of peripheral lesions. Peripheral OCT imaging helped elucidate clinically ambiguous situations such as retinal breaks, subclinical retinal detachment, retinoschisis, choroidal nevus, and metastasis. Limitations of such scanning included end-gaze nystagmus and far peripheral lesions. This first of its kind study demonstrates the feasibility of peripheral retinal OCT imaging and expands the spectrum of indications for which OCT scanning may be clinically useful.

In vivo sectional imaging of the retinal periphery using conventional optical coherence tomography systems.

Science.gov (United States)

Kothari, Abhishek; Narendran, V; Saravanan, V R

2012-01-01

Optical coherence tomography (OCT) has transformed macular disease practices. This report describes the use of conventional OCT systems for peripheral retinal imaging. Thirty-six eyes with peripheral retinal pathology underwent imaging with conventional OCT systems. In vivo sectional imaging of lattice degeneration, snail-track degeneration, and paving-stone degeneration was performed. Differences were noted between phenotypes of lattice degeneration. Several findings previously unreported in histopathology studies were encountered. Certain anatomic features were seen that could conceivably explain clinical and intraoperative behavior of peripheral lesions. Peripheral OCT imaging helped elucidate clinically ambiguous situations such as retinal breaks, subclinical retinal detachment, retinoschisis, choroidal nevus, and metastasis. Limitations of such scanning included end-gaze nystagmus and far peripheral lesions. This first of its kind study demonstrates the feasibility of peripheral retinal OCT imaging and expands the spectrum of indications for which OCT scanning may be clinically useful.

Imaging retinal progenitor lineages in developing zebrafish embryos.

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Jusuf, Patricia; Harris, William A; Poggi, Lucia

2013-03-01

In this protocol, we describe how to make and analyze four dimensional (4D) movies of retinal lineage in the zebrafish embryo in vivo. 4D consists of three spatial dimensions (3D) reconstructed from stacks of confocal planes plus one time dimension. Our imaging is performed on transgenic cells that express fluorescent proteins under the control of cell-specific promoters or on cells that transiently express such reporters in specific retinal cell progenitors. An important aspect of lineage tracing is the ability to follow individual cells as they undergo multiple cell divisions, final migration, and differentiation. This may mean many hours of 4D imaging, requiring that cells be kept healthy and maintained under conditions suitable for normal development. The longest movies we have made are ∼50 h. By analyzing these movies, we can see when a specific cell was born and who its sister was, allowing us to reconstruct its retinal lineages in vivo.

An automated retinal imaging method for the early diagnosis of diabetic retinopathy.

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Franklin, S Wilfred; Rajan, S Edward

2013-01-01

Diabetic retinopathy is a microvascular complication of long-term diabetes and is the major cause for eyesight loss due to changes in blood vessels of the retina. Major vision loss due to diabetic retinopathy is highly preventable with regular screening and timely intervention at the earlier stages. Retinal blood vessel segmentation methods help to identify the successive stages of such sight threatening diseases like diabetes. To develop and test a novel retinal imaging method which segments the blood vessels automatically from retinal images, which helps the ophthalmologists in the diagnosis and follow-up of diabetic retinopathy. This method segments each image pixel as vessel or nonvessel, which in turn, used for automatic recognition of the vasculature in retinal images. Retinal blood vessels were identified by means of a multilayer perceptron neural network, for which the inputs were derived from the Gabor and moment invariants-based features. Back propagation algorithm, which provides an efficient technique to change the weights in a feed forward network, is utilized in our method. Quantitative results of sensitivity, specificity and predictive values were obtained in our method and the measured accuracy of our segmentation algorithm was 95.3%, which is better than that presented by state-of-the-art approaches. The evaluation procedure used and the demonstrated effectiveness of our automated retinal imaging method proves itself as the most powerful tool to diagnose diabetic retinopathy in the earlier stages.

Roi Detection and Vessel Segmentation in Retinal Image

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Sabaz, F.; Atila, U.

2017-11-01

Diabetes disrupts work by affecting the structure of the eye and afterwards leads to loss of vision. Depending on the stage of disease that called diabetic retinopathy, there are sudden loss of vision and blurred vision problems. Automated detection of vessels in retinal images is a useful study to diagnose eye diseases, disease classification and other clinical trials. The shape and structure of the vessels give information about the severity of the disease and the stage of the disease. Automatic and fast detection of vessels allows for a quick diagnosis of the disease and the treatment process to start shortly. ROI detection and vessel extraction methods for retinal image are mentioned in this study. It is shown that the Frangi filter used in image processing can be successfully used in detection and extraction of vessels.

Automated imaging dark adaptometer for investigating hereditary retinal degenerations

Science.gov (United States)

Azevedo, Dario F. G.; Cideciyan, Artur V.; Regunath, Gopalakrishnan; Jacobson, Samuel G.

1995-05-01

We designed and built an automated imaging dark adaptometer (AIDA) to increase accuracy, reliability, versatility and speed of dark adaptation testing in patients with hereditary retinal degenerations. AIDA increases test accuracy by imaging the ocular fundus for precise positioning of bleaching and stimulus lights. It improves test reliability by permitting continuous monitoring of patient fixation. Software control of stimulus presentation provides broad testing versatility without sacrificing speed. AIDA promises to facilitate the measurement of dark adaptation in studies of the pathophysiology of retinal degenerations and in future treatment trials of these diseases.

Update on wide- and ultra-widefield retinal imaging

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Samir S Shoughy

2015-01-01

Full Text Available The peripheral retina is the site of pathology in many ocular diseases and ultra-widefield (UWF imaging is one of the new technologies available to ophthalmologists to manage some of these diseases. Currently, there are several imaging systems used in practice for the purpose of diagnostic, monitoring disease progression or response to therapy, and telemedicine. These include modalities for both adults and pediatric patients. The current systems are capable of producing wide- and UWF color fundus photographs, fluorescein and indocyanine green angiograms, and autofluorescence images. Using this technology, important clinical observations have been made in diseases such as diabetic retinopathy, uveitides, retinal vascular occlusions and tumors, intraocular tumors, retinopathy of prematurity, and age-related macular degeneration. Widefield imaging offers excellent postoperative documentation of retinal detachment surgery. New applications will soon be available to integrate this technology into large volume routine clinical practice.

Bioelectronic retinal prosthesis

Science.gov (United States)

Weiland, James D.

2016-05-01

Retinal prosthesis have been translated to clinical use over the past two decades. Currently, two devices have regulatory approval for the treatment of retinitis pigmentosa and one device is in clinical trials for treatment of age-related macular degeneration. These devices provide partial sight restoration and patients use this improved vision in their everyday lives to navigate and to detect large objects. However, significant vision restoration will require both better technology and improved understanding of the interaction between electrical stimulation and the retina. In particular, current retinal prostheses do not provide peripheral visions due to technical and surgical limitations, thus limiting the effectiveness of the treatment. This paper reviews recent results from human implant patients and presents technical approaches for peripheral vision.

All-optical recording and stimulation of retinal neurons in vivo in retinal degeneration mice

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Strazzeri, Jennifer M.; Williams, David R.; Merigan, William H.

2018-01-01

Here we demonstrate the application of a method that could accelerate the development of novel therapies by allowing direct and repeatable visualization of cellular function in the living eye, to study loss of vision in animal models of retinal disease, as well as evaluate the time course of retinal function following therapeutic intervention. We use high-resolution adaptive optics scanning light ophthalmoscopy to image fluorescence from the calcium sensor GCaMP6s. In mice with photoreceptor degeneration (rd10), we measured restored visual responses in ganglion cell layer neurons expressing the red-shifted channelrhodopsin ChrimsonR over a six-week period following significant loss of visual responses. Combining a fluorescent calcium sensor, a channelrhodopsin, and adaptive optics enables all-optical stimulation and recording of retinal neurons in the living eye. Because the retina is an accessible portal to the central nervous system, our method also provides a novel non-invasive method of dissecting neuronal processing in the brain. PMID:29596518

3D Reconstruction of the Retinal Arterial Tree Using Subject-Specific Fundus Images

Science.gov (United States)

Liu, D.; Wood, N. B.; Xu, X. Y.; Witt, N.; Hughes, A. D.; Samcg, Thom

Systemic diseases, such as hypertension and diabetes, are associated with changes in the retinal microvasculature. Although a number of studies have been performed on the quantitative assessment of the geometrical patterns of the retinal vasculature, previous work has been confined to 2 dimensional (2D) analyses. In this paper, we present an approach to obtain a 3D reconstruction of the retinal arteries from a pair of 2D retinal images acquired in vivo. A simple essential matrix based self-calibration approach was employed for the "fundus camera-eye" system. Vessel segmentation was performed using a semi-automatic approach and correspondence between points from different images was calculated. The results of 3D reconstruction show the centreline of retinal vessels and their 3D curvature clearly. Three-dimensional reconstruction of the retinal vessels is feasible and may be useful in future studies of the retinal vasculature in disease.

In vivo integrated photoacoustic ophthalmoscopy, optical coherence tomography, and scanning laser ophthalmoscopy for retinal imaging

Science.gov (United States)

Song, Wei; Zhang, Rui; Zhang, Hao F.; Wei, Qing; Cao, Wenwu

2012-12-01

The physiological and pathological properties of retina are closely associated with various optical contrasts. Hence, integrating different ophthalmic imaging technologies is more beneficial in both fundamental investigation and clinical diagnosis of several blinding diseases. Recently, photoacoustic ophthalmoscopy (PAOM) was developed for in vivo retinal imaging in small animals, which demonstrated the capability of imaging retinal vascular networks and retinal pigment epithelium (RPE) at high sensitivity. We combined PAOM with traditional imaging modalities, such as fluorescein angiography (FA), spectral-domain optical coherence tomography (SD-OCT), and auto-fluorescence scanning laser ophthalmoscopy (AF-SLO), for imaging rats and mice. The multimodal imaging system provided more comprehensive evaluation of the retina based on the complementary imaging contrast mechanisms. The high-quality retinal images show that the integrated ophthalmic imaging system has great potential in the investigation of blinding disorders.

Automatic detection of retinal exudates in fundus images of diabetic retinopathy patients

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Mahsa Partovi

2016-05-01

Full Text Available Introduction: Diabetic retinopathy (DR is the most frequent microvascular complication of diabetes and can lead to several retinal abnormalities including microaneurysms, exudates, dot and blot hemorrhages, and cotton wool spots. Automated early detection of these abnormalities could limit the severity of the disease and assist ophthalmologists in investigating and treating the disease more efficiently. Segmentation of retinal image features provides the basis for automated assessment. In this study, exudates lesion on retinopathy retinal images was segmented by different image processing techniques. The objective of this study is detection of the exudates regions on retinal images of retinopathy patients by different image processing techniques. Methods: A total of 30 color images from retinopathy patients were selected for this study. The images were taken by Topcon TRC-50 IX mydriatic camera and saves with TIFF format with a resolution of 500 × 752 pixels. The morphological function was applied on intensity components of hue saturation intensity (HSI space. To detect the exudates regions, thresholding was performed on all images and the exudates region was segmented. To optimize the detection efficiency, the binary morphological functions were applied. Finally, the exudates regions were quantified and evaluated for further statistical purposes. Results: The average of sensitivity of 76%, specificity of 98%, and accuracy of 97% was obtained. Conclusion: The results showed that our approach can identify the exudate regions in retinopathy images.

Outer Retinal and Choroidal Evaluation in Multiple Evanescent White Dot Syndrome (MEWDS): An Enhanced Depth Imaging Optical Coherence Tomography Study.

Science.gov (United States)

Fiore, Tito; Iaccheri, Barbara; Cerquaglia, Alessio; Lupidi, Marco; Torroni, Giovanni; Fruttini, Daniela; Cagini, Carlo

2018-01-01

To perform an analysis of optical coherence tomography (OCT) abnormalities in patients with MEWDS, during the acute and recovery stages, using enhanced depth imaging-OCT (EDI-OCT). A retrospective case series of five patients with MEWDS was included. EDI-OCT imaging was evaluated to detect retinal and choroidal features. In the acute phase, focal impairment of the ellipsoid zone and external limiting membrane, hyperreflective dots in the inner choroid, and full-thickness increase of the choroidal profile were observed in the affected eye; disappearance of these findings and restoration of the choroidal thickness (p = 0.046) was appreciated in the recovery phase. No OCT abnormalities were assessed in the unaffected eye. EDI-OCT revealed transient outer retinal layer changes and inner choroidal hyperreflective dots. A transient increased thickness of the whole choroid was also identified. This might confirm a short-lasting inflammatory involvement of the whole choroidal tissue in the active phase of MEWDS.

A Method for Combined Retinal Vascular and Tissue Oxygen Tension Imaging.

Science.gov (United States)

Felder, Anthony E; Wanek, Justin; Tan, Michael R; Blair, Norman P; Shahidi, Mahnaz

2017-09-06

The retina requires adequate oxygenation to maintain cellular metabolism and visual function. Inner retinal oxygen metabolism is directly related to retinal vascular oxygen tension (PO 2 ) and inner retinal oxygen extraction fraction (OEF), whereas outer retinal oxygen consumption (QO 2 ) relies on oxygen availability by the choroid and is contingent upon retinal tissue oxygen tension (tPO 2 ) gradients across the retinal depth. Thus far, these oxygenation and metabolic parameters have been measured independently by different techniques in separate animals, precluding a comprehensive and correlative assessment of retinal oxygenation and metabolism dynamics. The purpose of the current study is to report an innovative optical system for dual oxyphor phosphorescence lifetime imaging to near-simultaneously measure retinal vascular PO 2 and tPO 2 in rats. The use of a new oxyphor with different spectral characteristics allowed differentiation of phosphorescence signals from the retinal vasculature and tissue. Concurrent measurements of retinal arterial and venous PO 2 , tPO 2 through the retinal depth, inner retinal OEF, and outer retinal QO 2 were demonstrated, permitting a correlative assessment of retinal oxygenation and metabolism. Future application of this method can be used to investigate the relations among retinal oxygen content, extraction and metabolism under pathologic conditions and thus advance knowledge of retinal hypoxia pathophysiology.

ROI DETECTION AND VESSEL SEGMENTATION IN RETINAL IMAGE

Directory of Open Access Journals (Sweden)

F. Sabaz

2017-11-01

Full Text Available Diabetes disrupts work by affecting the structure of the eye and afterwards leads to loss of vision. Depending on the stage of disease that called diabetic retinopathy, there are sudden loss of vision and blurred vision problems. Automated detection of vessels in retinal images is a useful study to diagnose eye diseases, disease classification and other clinical trials. The shape and structure of the vessels give information about the severity of the disease and the stage of the disease. Automatic and fast detection of vessels allows for a quick diagnosis of the disease and the treatment process to start shortly. ROI detection and vessel extraction methods for retinal image are mentioned in this study. It is shown that the Frangi filter used in image processing can be successfully used in detection and extraction of vessels.

Restoration of longitudinal images.

Science.gov (United States)

Hu, Y; Frieden, B R

1988-01-15

In this paper, a method of restoring longitudinal images is developed. By using the transfer function for longitudinal objects, and inverse filtering, a longitudinal image may be restored. The Fourier theory and sampling theorems for transverse images cannot be used directly in the longitudinal case. A modification and reasonable approximation are introduced. We have numerically established a necessary relationship between just-resolved longitudinal separation (after inverse filtering), noise level, and the taking conditions of object distance and lens diameter. An empirical formula is also found to well-fit the computed results. This formula may be of use for designing optical systems which are to image longitudinal details, such as in robotics or microscopy.

Photovoltaic restoration of sight with high visual acuity

Science.gov (United States)

Lorach, Henri; Goetz, Georges; Smith, Richard; Lei, Xin; Mandel, Yossi; Kamins, Theodore; Mathieson, Keith; Huie, Philip; Harris, James; Sher, Alexander; Palanker, Daniel

2015-01-01

Patients with retinal degeneration lose sight due to gradual demise of photoreceptors. Electrical stimulation of the surviving retinal neurons provides an alternative route for delivery of visual information. We demonstrate that subretinal arrays with 70 μm photovoltaic pixels provide highly localized stimulation, with electrical and visual receptive fields of comparable sizes in rat retinal ganglion cells. Similarly to normal vision, retinal response to prosthetic stimulation exhibits flicker fusion at high frequencies, adaptation to static images and non-linear spatial summation. In rats with retinal degeneration, these photovoltaic arrays provide spatial resolution of 64 ± 11 μm, corresponding to half of the normal visual acuity in pigmented rats. Ease of implantation of these wireless and modular arrays, combined with their high resolution opens the door to functional restoration of sight. PMID:25915832

Generalized probabilistic scale space for image restoration.

Science.gov (United States)

Wong, Alexander; Mishra, Akshaya K

2010-10-01

A novel generalized sampling-based probabilistic scale space theory is proposed for image restoration. We explore extending the definition of scale space to better account for both noise and observation models, which is important for producing accurately restored images. A new class of scale-space realizations based on sampling and probability theory is introduced to realize this extended definition in the context of image restoration. Experimental results using 2-D images show that generalized sampling-based probabilistic scale-space theory can be used to produce more accurate restored images when compared with state-of-the-art scale-space formulations, particularly under situations characterized by low signal-to-noise ratios and image degradation.

An optimized content-aware image retargeting method: toward expanding the perceived visual field of the high-density retinal prosthesis recipients

Science.gov (United States)

Li, Heng; Zeng, Yajie; Lu, Zhuofan; Cao, Xiaofei; Su, Xiaofan; Sui, Xiaohong; Wang, Jing; Chai, Xinyu

2018-04-01

Objective. Retinal prosthesis devices have shown great value in restoring some sight for individuals with profoundly impaired vision, but the visual acuity and visual field provided by prostheses greatly limit recipients’ visual experience. In this paper, we employ computer vision approaches to seek to expand the perceptible visual field in patients implanted potentially with a high-density retinal prosthesis while maintaining visual acuity as much as possible. Approach. We propose an optimized content-aware image retargeting method, by introducing salient object detection based on color and intensity-difference contrast, aiming to remap important information of a scene into a small visual field and preserve their original scale as much as possible. It may improve prosthetic recipients’ perceived visual field and aid in performing some visual tasks (e.g. object detection and object recognition). To verify our method, psychophysical experiments, detecting object number and recognizing objects, are conducted under simulated prosthetic vision. As control, we use three other image retargeting techniques, including Cropping, Scaling, and seam-assisted shrinkability. Main results. Results show that our method outperforms in preserving more key features and has significantly higher recognition accuracy in comparison with other three image retargeting methods under the condition of small visual field and low-resolution. Significance. The proposed method is beneficial to expand the perceived visual field of prosthesis recipients and improve their object detection and recognition performance. It suggests that our method may provide an effective option for image processing module in future high-density retinal implants.

Joint image restoration and location in visual navigation system

Science.gov (United States)

Wu, Yuefeng; Sang, Nong; Lin, Wei; Shao, Yuanjie

2018-02-01

Image location methods are the key technologies of visual navigation, most previous image location methods simply assume the ideal inputs without taking into account the real-world degradations (e.g. low resolution and blur). In view of such degradations, the conventional image location methods first perform image restoration and then match the restored image on the reference image. However, the defective output of the image restoration can affect the result of localization, by dealing with the restoration and location separately. In this paper, we present a joint image restoration and location (JRL) method, which utilizes the sparse representation prior to handle the challenging problem of low-quality image location. The sparse representation prior states that the degraded input image, if correctly restored, will have a good sparse representation in terms of the dictionary constructed from the reference image. By iteratively solving the image restoration in pursuit of the sparest representation, our method can achieve simultaneous restoration and location. Based on such a sparse representation prior, we demonstrate that the image restoration task and the location task can benefit greatly from each other. Extensive experiments on real scene images with Gaussian blur are carried out and our joint model outperforms the conventional methods of treating the two tasks independently.

Incorporating Spatial Information for Microaneurysm Detection in Retinal Images

Directory of Open Access Journals (Sweden)

Mohamed M. Habib

2017-06-01

Full Text Available The presence of microaneurysms(MAs in retinal images is a pathognomonic sign of Diabetic Retinopathy (DR. This is one of the leading causes of blindness in the working population worldwide. This paper introduces a novel algorithm that combines information from spatial views of the retina for the purpose of MA detection. Most published research in the literature has addressed the problem of detecting MAs from single retinal images. This work proposes the incorporation of information from two spatial views during the detection process. The algorithm is evaluated using 160 images from 40 patients seen as part of a UK diabetic eye screening programme which contained 207 MAs. An improvement in performance compared to detection from an algorithm that relies on a single image is shown as an increase of 2% ROC score, hence demonstrating the potential of this method.

Cell Therapy Applications for Retinal Vascular Diseases: Diabetic Retinopathy and Retinal Vein Occlusion.

Science.gov (United States)

Park, Susanna S

2016-04-01

Retinal vascular conditions, such as diabetic retinopathy and retinal vein occlusion, remain leading causes of vision loss. No therapy exists to restore vision loss resulting from retinal ischemia and associated retinal degeneration. Tissue regeneration is possible with cell therapy. The goal would be to restore or replace the damaged retinal vasculature and the retinal neurons that are damaged and/or degenerating from the hypoxic insult. Currently, various adult cell therapies have been explored as potential treatment. They include mesenchymal stem cells, vascular precursor cells (i.e., CD34+ cells, hematopoietic cells or endothelial progenitor cells), and adipose stromal cells. Preclinical studies show that all these cells have a paracrine trophic effect on damaged ischemic tissue, leading to tissue preservation. Endothelial progenitor cells and adipose stromal cells integrate into the damaged retinal vascular wall in preclinical models of diabetic retinopathy and ischemia-reperfusion injury. Mesenchymal stem cells do not integrate as readily but appear to have a primary paracrine trophic effect. Early phase clinical trials have been initiated and ongoing using mesenchymal stem cells or autologous bone marrow CD34+ cells injected intravitreally as potential therapy for diabetic retinopathy or retinal vein occlusion. Adipose stromal cells or pluripotent stem cells differentiated into endothelial colony-forming cells have been explored in preclinical studies and show promise as possible therapies for retinal vascular disorders. The relative safety or efficacy of these various cell therapies for treating retinal vascular disorders have yet to be determined.

Real-time emulation of neural images in the outer retinal circuit.

Science.gov (United States)

Hasegawa, Jun; Yagi, Tetsuya

2008-12-01

We describe a novel real-time system that emulates the architecture and functionality of the vertebrate retina. This system reconstructs the neural images formed by the retinal neurons in real time by using a combination of analog and digital systems consisting of a neuromorphic silicon retina chip, a field-programmable gate array, and a digital computer. While the silicon retina carries out the spatial filtering of input images instantaneously, using the embedded resistive networks that emulate the receptive field structure of the outer retinal neurons, the digital computer carries out the temporal filtering of the spatially filtered images to emulate the dynamical properties of the outer retinal circuits. The emulations of the neural image, including 128 x 128 bipolar cells, are carried out at a frame rate of 62.5 Hz. The emulation of the response to the Hermann grid and a spot of light and an annulus of lights has demonstrated that the system responds as expected by previous physiological and psychophysical observations. Furthermore, the emulated dynamics of neural images in response to natural scenes revealed the complex nature of retinal neuron activity. We have concluded that the system reflects the spatiotemporal responses of bipolar cells in the vertebrate retina. The proposed emulation system is expected to aid in understanding the visual computation in the retina and the brain.

Two-dimensional maximum entropy image restoration

International Nuclear Information System (INIS)

Brolley, J.E.; Lazarus, R.B.; Suydam, B.R.; Trussell, H.J.

1977-07-01

An optical check problem was constructed to test P LOG P maximum entropy restoration of an extremely distorted image. Useful recovery of the original image was obtained. Comparison with maximum a posteriori restoration is made. 7 figures

Landmark matching based retinal image alignment by enforcing sparsity in correspondence matrix.

Science.gov (United States)

Zheng, Yuanjie; Daniel, Ebenezer; Hunter, Allan A; Xiao, Rui; Gao, Jianbin; Li, Hongsheng; Maguire, Maureen G; Brainard, David H; Gee, James C

2014-08-01

Retinal image alignment is fundamental to many applications in diagnosis of eye diseases. In this paper, we address the problem of landmark matching based retinal image alignment. We propose a novel landmark matching formulation by enforcing sparsity in the correspondence matrix and offer its solutions based on linear programming. The proposed formulation not only enables a joint estimation of the landmark correspondences and a predefined transformation model but also combines the benefits of the softassign strategy (Chui and Rangarajan, 2003) and the combinatorial optimization of linear programming. We also introduced a set of reinforced self-similarities descriptors which can better characterize local photometric and geometric properties of the retinal image. Theoretical analysis and experimental results with both fundus color images and angiogram images show the superior performances of our algorithms to several state-of-the-art techniques. Copyright © 2013 Elsevier B.V. All rights reserved.

Lesion detection in ultra-wide field retinal images for diabetic retinopathy diagnosis

Science.gov (United States)

Levenkova, Anastasia; Sowmya, Arcot; Kalloniatis, Michael; Ly, Angelica; Ho, Arthur

2018-02-01

Diabetic retinopathy (DR) leads to irreversible vision loss. Diagnosis and staging of DR is usually based on the presence, number, location and type of retinal lesions. Ultra-wide field (UWF) digital scanning laser technology provides an opportunity for computer-aided DR lesion detection. High-resolution UWF images (3078×2702 pixels) may allow detection of more clinically relevant retinopathy in comparison with conventional retinal images as UWF imaging covers a 200° retinal area, versus 45° by conventional cameras. Current approaches to DR diagnosis that analyze 7-field Early Treatment Diabetic Retinopathy Study (ETDRS) retinal images provide similar results to UWF imaging. However, in 40% of cases, more retinopathy was found outside the 7- field ETDRS fields by UWF and in 10% of cases, retinopathy was reclassified as more severe. The reason is that UWF images examine both the central retina and more peripheral regions. We propose an algorithm for automatic detection and classification of DR lesions such as cotton wool spots, exudates, microaneurysms and haemorrhages in UWF images. The algorithm uses convolutional neural network (CNN) as a feature extractor and classifies the feature vectors extracted from colour-composite UWF images using a support vector machine (SVM). The main contribution includes detection of four types of DR lesions in the peripheral retina for diagnostic purposes. The evaluation dataset contains 146 UWF images. The proposed method for detection of DR lesion subtypes in UWF images using two scenarios for transfer learning achieved AUC ≈ 80%. Data was split at the patient level to validate the proposed algorithm.

Automatic segmentation of blood vessels from retinal fundus images ...

Indian Academy of Sciences (India)

The retinal blood vessels were segmented through color space conversion and color channel extraction, image pre-processing, Gabor filtering, image postprocessing, feature construction through application of principal component analysis, k-means clustering and first level classification using Naïve–Bayes classification ...

Adaptive optics with pupil tracking for high resolution retinal imaging.

Science.gov (United States)

Sahin, Betul; Lamory, Barbara; Levecq, Xavier; Harms, Fabrice; Dainty, Chris

2012-02-01

Adaptive optics, when integrated into retinal imaging systems, compensates for rapidly changing ocular aberrations in real time and results in improved high resolution images that reveal the photoreceptor mosaic. Imaging the retina at high resolution has numerous potential medical applications, and yet for the development of commercial products that can be used in the clinic, the complexity and high cost of the present research systems have to be addressed. We present a new method to control the deformable mirror in real time based on pupil tracking measurements which uses the default camera for the alignment of the eye in the retinal imaging system and requires no extra cost or hardware. We also present the first experiments done with a compact adaptive optics flood illumination fundus camera where it was possible to compensate for the higher order aberrations of a moving model eye and in vivo in real time based on pupil tracking measurements, without the real time contribution of a wavefront sensor. As an outcome of this research, we showed that pupil tracking can be effectively used as a low cost and practical adaptive optics tool for high resolution retinal imaging because eye movements constitute an important part of the ocular wavefront dynamics.

Structural analysis of retinal photoreceptor ellipsoid zone and postreceptor retinal layer associated with visual acuity in patients with retinitis pigmentosa by ganglion cell analysis combined with OCT imaging

Science.gov (United States)

Liu, Guodong; Li, Hui; Liu, Xiaoqiang; Xu, Ding; Wang, Fang

2016-01-01

Abstract The aim of this study was to examine changes in photoreceptor ellipsoid zone (EZ) and postreceptor retinal layer in retinitis pigmentosa (RP) patients by ganglion cell analysis (GCA) combined with optical coherence tomography (OCT) imaging to evaluate the structure–function relationships between retinal layer changes and best corrected visual acuity (BCVA). Sixty-eight eyes of 35 patients with RP and 65 eyes of 35 normal controls were analyzed in the study. The average length of EZ was 911.1 ± 208.8 μm in RP patients, which was shortened with the progression of the disease on the OCT images. The average ganglion cell–inner plexiform layer thickness (GCIPLT) was 54.7 ± 18.9 μm in RP patients, while in normal controls it was 85.6 ± 6.8 μm. The GCIPLT in all quarters became significantly thinner along with outer retinal thinning. There was a significantly positive correlation between BCVA and EZ (r = −0.7622, P retinal layer changes from a new perspective in RP patients, which suggests that EZ and GCIPLT obtained by GCA combined with OCT imaging are the direct and valid indicators to diagnosis and predict the pathological process of RP. PMID:28033301

Reduced-illuminance autofluorescence imaging in ABCA4-associated retinal degenerations

Science.gov (United States)

Cideciyan, Artur V.; Swider, Malgorzata; Aleman, Tomas S.; Roman, Marisa I.; Sumaroka, Alexander; Schwartz, Sharon B.; Stone, Edwin M.; Jacobson, Samuel G.

2007-05-01

The health of the retinal pigment epithelium (RPE) can be estimated with autofluorescence (AF) imaging of lipofuscin, which accumulates as a byproduct of retinal exposure to light. Lipofuscin may be toxic to the RPE, and its toxicity may be enhanced by short-wavelength (SW) illumination. The high-intensity and SW excitation light used in conventional AF imaging could, at least in principle, increase the rate of lipofuscin accumulation and/or increase its toxicity. We considered two reduced-illuminance AF imaging (RAFI) methods as alternatives to conventional AF imaging. RAFI methods use either near-infrared (NIR) light or reduced-radiance SW illumination for excitation of fluorophores. We quantified the distribution of RAFI signals in relation to retinal structure and function in patients with the prototypical lipofuscin accumulation disease caused by mutations in ABCA4. There was evidence for two subclinical stages of macular ABCA4 disease involving hyperautofluorescence of both SW- and NIR-RAFI with and without associated loss of visual function. Use of RAFI methods and microperimetry in future clinical trials involving lipofuscinopathies should allow quantification of subclinical disease expression and progression without subjecting the diseased retina/RPE to undue light exposure.

Models for Patch-Based Image Restoration

Directory of Open Access Journals (Sweden)

Petrovic Nemanja

2009-01-01

Full Text Available Abstract We present a supervised learning approach for object-category specific restoration, recognition, and segmentation of images which are blurred using an unknown kernel. The novelty of this work is a multilayer graphical model which unifies the low-level vision task of restoration and the high-level vision task of recognition in a cooperative framework. The graphical model is an interconnected two-layer Markov random field. The restoration layer accounts for the compatibility between sharp and blurred images and models the association between adjacent patches in the sharp image. The recognition layer encodes the entity class and its location in the underlying scene. The potentials are represented using nonparametric kernel densities and are learnt from training data. Inference is performed using nonparametric belief propagation. Experiments demonstrate the effectiveness of our model for the restoration and recognition of blurred license plates as well as face images.

Models for Patch-Based Image Restoration

Directory of Open Access Journals (Sweden)

Mithun Das Gupta

2009-01-01

Full Text Available We present a supervised learning approach for object-category specific restoration, recognition, and segmentation of images which are blurred using an unknown kernel. The novelty of this work is a multilayer graphical model which unifies the low-level vision task of restoration and the high-level vision task of recognition in a cooperative framework. The graphical model is an interconnected two-layer Markov random field. The restoration layer accounts for the compatibility between sharp and blurred images and models the association between adjacent patches in the sharp image. The recognition layer encodes the entity class and its location in the underlying scene. The potentials are represented using nonparametric kernel densities and are learnt from training data. Inference is performed using nonparametric belief propagation. Experiments demonstrate the effectiveness of our model for the restoration and recognition of blurred license plates as well as face images.

Non-invasive imaging of retinal blood flow in myeloproliferative neoplasms

DEFF Research Database (Denmark)

Willerslev, Anne; Hansen, Mathias M; Klefter, Oliver Niels

2017-01-01

PURPOSE: To study the circulation in the retinal vessels in patients with blood dyscrasia due to myeloproliferative neoplasms using non-invasive retinal imaging. METHODS: Prospective consecutive case series of seven treatment-naïve patients with chronic myeloid leukaemia (n = 2), polycythemia vera...... present at baseline in patients with chronic myeloid leukaemia and were replaced by normal patterns at follow-up. Retinopathy, in the form of cotton-wool spots and retinal haemorrhages, was found at presentation in the two patients with chronic myeloid leukaemia and in one patient with polycythemia vera...

A thresholding based technique to extract retinal blood vessels from fundus images

Directory of Open Access Journals (Sweden)

Jyotiprava Dash

2017-12-01

Full Text Available Retinal imaging has become the significant tool among all the medical imaging technology, due to its capability to extract many data which is linked to various eye diseases. So, the accurate extraction of blood vessel is necessary that helps the eye care specialists and ophthalmologist to identify the diseases at the early stages. In this paper, we have proposed a computerized technique for extraction of blood vessels from fundus images. The process is conducted in three phases: (i pre-processing where the image is enhanced using contrast limited adaptive histogram equalization and median filter, (ii segmentation using mean-C thresholding to extract retinal blood vessels, (iii post-processing where morphological cleaning operation is used to remove isolated pixels. The performance of the proposed method is tested on and experimental results show that our method achieve an accuracies of 0.955 and 0.954 on Digital retinal images for vessel extraction (DRIVE and Child heart and health study in England (CHASE_DB1 databases respectively.

MULTIMODAL IMAGING OF DISEASE-ASSOCIATED PIGMENTARY CHANGES IN RETINITIS PIGMENTOSA.

Science.gov (United States)

Schuerch, Kaspar; Marsiglia, Marcela; Lee, Winston; Tsang, Stephen H; Sparrow, Janet R

2016-12-01

Using multiple imaging modalities, we evaluated the changes in photoreceptor cells and retinal pigment epithelium (RPE) that are associated with bone spicule-shaped melanin pigmentation in retinitis pigmentosa. In a cohort of 60 patients with retinitis pigmentosa, short-wavelength autofluorescence, near-infrared autofluorescence (NIR-AF), NIR reflectance, spectral domain optical coherence tomography, and color fundus images were studied. Central AF rings were visible in both short-wavelength autofluorescence and NIR-AF images. Bone spicule pigmentation was nonreflective in NIR reflectance, hypoautofluorescent with short-wavelength autofluorescence and NIR-AF imaging, and presented as intraretinal hyperreflective foci in spectral domain optical coherence tomography images. In areas beyond the AF ring outer border, the photoreceptor ellipsoid zone band was absent in spectral domain optical coherence tomography and the visibility of choroidal vessels in short-wavelength autofluorescence, NIR-AF, and NIR reflectance images was indicative of reduced RPE pigmentation. Choroidal visibility was most pronounced in the zone approaching peripheral areas of bone spicule pigmentation; here RPE/Bruch membrane thinning became apparent in spectral domain optical coherence tomography. These findings are consistent with a process by which RPE cells vacate their monolayer and migrate into inner retina in response to photoreceptor cell degeneration. The remaining RPE spread undergo thinning and consequently become less pigmented. An explanation for the absence of NIR-AF melanin signal in relation to bone spicule pigmentation is not forthcoming.

Discriminative Transfer Learning for General Image Restoration

KAUST Repository

Xiao, Lei; Heide, Felix; Heidrich, Wolfgang; Schö lkopf, Bernhard; Hirsch, Michael

2018-01-01

Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

Discriminative Transfer Learning for General Image Restoration

KAUST Repository

Xiao, Lei

2018-04-30

Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

Effect of software manipulation (Photoshop) of digitised retinal images on the grading of diabetic retinopathy.

Science.gov (United States)

George, L D; Lusty, J; Owens, D R; Ollerton, R L

1999-08-01

To determine whether software processing of digitised retinal images using a "sharpen" filter improves the ability to grade diabetic retinopathy. 150 macula centred retinal images were taken as 35 mm colour transparencies representing a spectrum of diabetic retinopathy, digitised, and graded in random order before and after the application of a sharpen filter (Adobe Photoshop). Digital enhancement of contrast and brightness was performed and a X2 digital zoom was utilised. The grades from the unenhanced and enhanced digitised images were compared with the same retinal fields viewed as slides. Overall agreement in retinopathy grade from the digitised images improved from 83.3% (125/150) to 94.0% (141/150) with sight threatening diabetic retinopathy (STDR) correctly identified in 95.5% (84/88) and 98.9% (87/88) of cases when using unenhanced and enhanced images respectively. In total, five images were overgraded and four undergraded from the enhanced images compared with 17 and eight images respectively when using unenhanced images. This study demonstrates that the already good agreement in grading performance can be further improved by software manipulation or processing of digitised retinal images.

Progress toward the maintenance and repair of degenerating retinal circuitry.

Science.gov (United States)

Vugler, Anthony A

2010-01-01

Retinal diseases such as age-related macular degeneration and retinitis pigmentosa remain major causes of severe vision loss in humans. Clinical trials for treatment of retinal degenerations are underway and advancements in our understanding of retinal biology in health/disease have implications for novel therapies. A review of retinal biology is used to inform a discussion of current strategies to maintain/repair neural circuitry in age-related macular degeneration, retinitis pigmentosa, and Type 2 Leber congenital amaurosis. In age-related macular degeneration/retinitis pigmentosa, a progressive loss of rods/cones results in corruption of bipolar cell circuitry, although retinal output neurons/photoreceptive melanopsin cells survive. Visual function can be stabilized/enhanced after treatment in age-related macular degeneration, but in advanced degenerations, reorganization of retinal circuitry may preclude attempts to restore cone function. In Type 2 Leber congenital amaurosis, useful vision can be restored by gene therapy where central cones survive. Remarkable progress has been made in restoring vision to rodents using light-responsive ion channels inserted into bipolar cells/retinal ganglion cells. Advances in genetic, cellular, and prosthetic therapies show varying degrees of promise for treating retinal degenerations. While functional benefits can be obtained after early therapeutic interventions, efforts should be made to minimize circuitry changes as soon as possible after rod/cone loss. Advances in retinal anatomy/physiology and genetic technologies should allow refinement of future reparative strategies.

Objective and expert-independent validation of retinal image registration algorithms by a projective imaging distortion model

NARCIS (Netherlands)

Lee, Sangyeol; Reinhardt, Joseph M.; Cattin, Philippe C.; Abramoff, M.D.

2010-01-01

Fundus camera imaging of the retina is widely used to diagnose and manage ophthalmologic disorders including diabetic retinopathy, glaucoma, and age-related macular degeneration. Retinal images typically have a limited field of view, and multiple images can be joined together using an image

Coupled dictionary learning for joint MR image restoration and segmentation

Science.gov (United States)

Yang, Xuesong; Fan, Yong

2018-03-01

To achieve better segmentation of MR images, image restoration is typically used as a preprocessing step, especially for low-quality MR images. Recent studies have demonstrated that dictionary learning methods could achieve promising performance for both image restoration and image segmentation. These methods typically learn paired dictionaries of image patches from different sources and use a common sparse representation to characterize paired image patches, such as low-quality image patches and their corresponding high quality counterparts for the image restoration, and image patches and their corresponding segmentation labels for the image segmentation. Since learning these dictionaries jointly in a unified framework may improve the image restoration and segmentation simultaneously, we propose a coupled dictionary learning method to concurrently learn dictionaries for joint image restoration and image segmentation based on sparse representations in a multi-atlas image segmentation framework. Particularly, three dictionaries, including a dictionary of low quality image patches, a dictionary of high quality image patches, and a dictionary of segmentation label patches, are learned in a unified framework so that the learned dictionaries of image restoration and segmentation can benefit each other. Our method has been evaluated for segmenting the hippocampus in MR T1 images collected with scanners of different magnetic field strengths. The experimental results have demonstrated that our method achieved better image restoration and segmentation performance than state of the art dictionary learning and sparse representation based image restoration and image segmentation methods.

Active learning approach for detection of hard exudates, cotton wool spots, and drusen in retinal images

Science.gov (United States)

Sánchez, Clara I.; Niemeijer, Meindert; Kockelkorn, Thessa; Abràmoff, Michael D.; van Ginneken, Bram

2009-02-01

Computer-aided Diagnosis (CAD) systems for the automatic identification of abnormalities in retinal images are gaining importance in diabetic retinopathy screening programs. A huge amount of retinal images are collected during these programs and they provide a starting point for the design of machine learning algorithms. However, manual annotations of retinal images are scarce and expensive to obtain. This paper proposes a dynamic CAD system based on active learning for the automatic identification of hard exudates, cotton wool spots and drusen in retinal images. An uncertainty sampling method is applied to select samples that need to be labeled by an expert from an unlabeled set of 4000 retinal images. It reduces the number of training samples needed to obtain an optimum accuracy by dynamically selecting the most informative samples. Results show that the proposed method increases the classification accuracy compared to alternative techniques, achieving an area under the ROC curve of 0.87, 0.82 and 0.78 for the detection of hard exudates, cotton wool spots and drusen, respectively.

Ghost suppression in image restoration filtering

Science.gov (United States)

Riemer, T. E.; Mcgillem, C. D.

1975-01-01

An optimum image restoration filter is described in which provision is made to constrain the spatial extent of the restoration function, the noise level of the filter output and the rate of falloff of the composite system point-spread away from the origin. Experimental results show that sidelobes on the composite system point-spread function produce ghosts in the restored image near discontinuities in intensity level. By redetermining the filter using a penalty function that is zero over the main lobe of the composite point-spread function of the optimum filter and nonzero where the point-spread function departs from a smoothly decaying function in the sidelobe region, a great reduction in sidelobe level is obtained. Almost no loss in resolving power of the composite system results from this procedure. By iteratively carrying out the same procedure even further reductions in sidelobe level are obtained. Examples of original and iterated restoration functions are shown along with their effects on a test image.

Spectral imaging technique for retinal perfusion detection using confocal scanning laser ophthalmoscopy

Science.gov (United States)

Rasta, Seyed Hossein; Manivannan, Ayyakkannu; Sharp, Peter F.

2012-11-01

To evaluate retinal perfusion in the human eye, a dual-wavelength confocal scanning laser ophthalmoscope (cSLO) was developed that provides spectral imaging of the fundus using a combination of red (670 nm) and near-infrared (810 nm) wavelengths. The image of the ocular fundus was analyzed to find out if quantitative measurements of the reflectivity of tissue permit assessment of the oxygen perfusion of tissue. We explored problems that affect the reproducibility of patient measurements such as non-uniformity errors on the image. For the first time, an image processing technique was designed and used to minimize the errors of oxygen saturation measurements by illumination correction in retina wide field by increasing SNR. Retinal images were taken from healthy and diabetic retinopathy eyes using the cSLO with a confocal aperture of 100 μm. The ratio image (RI) of red/IR, as oxygen saturation (SO2) index, was calculated for normal eyes. The image correction technique improved the reproducibility of the measurements. Average RI intensity variation of healthy retina tissue was determined within a range of about 5.5%. The capability of the new technique to discriminate oxygenation levels of retinal artery and vein was successfully demonstrated and showed good promise in the diagnosis of the perfused retina.

Comparative study of image restoration techniques in forensic image processing

Science.gov (United States)

Bijhold, Jurrien; Kuijper, Arjan; Westhuis, Jaap-Harm

1997-02-01

In this work we investigated the forensic applicability of some state-of-the-art image restoration techniques for digitized video-images and photographs: classical Wiener filtering, constrained maximum entropy, and some variants of constrained minimum total variation. Basic concepts and experimental results are discussed. Because all methods appeared to produce different results, a discussion is given of which method is the most suitable, depending on the image objects that are questioned, prior knowledge and type of blur and noise. Constrained minimum total variation methods produced the best results for test images with simulated noise and blur. In cases where images are the most substantial part of the evidence, constrained maximum entropy might be more suitable, because its theoretical basis predicts a restoration result that shows the most likely pixel values, given all the prior knowledge used during restoration.

An automated algorithm for photoreceptors counting in adaptive optics retinal images

Science.gov (United States)

Liu, Xu; Zhang, Yudong; Yun, Dai

2012-10-01

Eyes are important organs of humans that detect light and form spatial and color vision. Knowing the exact number of cones in retinal image has great importance in helping us understand the mechanism of eyes' function and the pathology of some eye disease. In order to analyze data in real time and process large-scale data, an automated algorithm is designed to label cone photoreceptors in adaptive optics (AO) retinal images. Images acquired by the flood-illuminated AO system are taken to test the efficiency of this algorithm. We labeled these images both automatically and manually, and compared the results of the two methods. A 94.1% to 96.5% agreement rate between the two methods is achieved in this experiment, which demonstrated the reliability and efficiency of the algorithm.

Laser speckle imaging of rat retinal blood flow with hybrid temporal and spatial analysis method

Science.gov (United States)

Cheng, Haiying; Yan, Yumei; Duong, Timothy Q.

2009-02-01

Noninvasive monitoring of blood flow in retinal circulation will reveal the progression and treatment of ocular disorders, such as diabetic retinopathy, age-related macular degeneration and glaucoma. A non-invasive and direct BF measurement technique with high spatial-temporal resolution is needed for retinal imaging. Laser speckle imaging (LSI) is such a method. Currently, there are two analysis methods for LSI: spatial statistics LSI (SS-LSI) and temporal statistical LSI (TS-LSI). Comparing these two analysis methods, SS-LSI has higher signal to noise ratio (SNR) and TSLSI is less susceptible to artifacts from stationary speckle. We proposed a hybrid temporal and spatial analysis method (HTS-LSI) to measure the retinal blood flow. Gas challenge experiment was performed and images were analyzed by HTS-LSI. Results showed that HTS-LSI can not only remove the stationary speckle but also increase the SNR. Under 100% O2, retinal BF decreased by 20-30%. This was consistent with the results observed with laser Doppler technique. As retinal blood flow is a critical physiological parameter and its perturbation has been implicated in the early stages of many retinal diseases, HTS-LSI will be an efficient method in early detection of retina diseases.

Restoration of motion-blurred image based on border deformation detection: a traffic sign restoration model.

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Yiliang Zeng

Full Text Available Due to the rapid development of motor vehicle Driver Assistance Systems (DAS, the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently.

Extraspectral Imaging for Improving the Perceived Information Presented in Retinal Prosthesis

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Walid Al-Atabany

2018-01-01

Full Text Available Retinal prosthesis is steadily improving as a clinical treatment for blindness caused by retinitis pigmentosa. However, despite the continued exciting progress, the level of visual return is still very poor. It is also unlikely that those utilising these devices will stop being legally blind in the near future. Therefore, it is important to develop methods to maximise the transfer of useful information extracted from the visual scene. Such an approach can be achieved by digitally suppressing less important visual features and textures within the scene. The result can be interpreted as a cartoon-like image of the scene. Furthermore, utilising extravisual wavelengths such as infrared can be useful in the decision process to determine the optimal information to present. In this paper, we, therefore, present a processing methodology that utilises information extracted from the infrared spectrum to assist in the preprocessing of the visual image prior to conversion to retinal information. We demonstrate how this allows for enhanced recognition and how it could be implemented for optogenetic forms of retinal prosthesis. The new approach has been quantitatively evaluated on volunteers showing 112% enhancement in recognizing objects over normal approaches.

Shift-invariant discrete wavelet transform analysis for retinal image classification.

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Khademi, April; Krishnan, Sridhar

2007-12-01

This work involves retinal image classification and a novel analysis system was developed. From the compressed domain, the proposed scheme extracts textural features from wavelet coefficients, which describe the relative homogeneity of localized areas of the retinal images. Since the discrete wavelet transform (DWT) is shift-variant, a shift-invariant DWT was explored to ensure that a robust feature set was extracted. To combat the small database size, linear discriminant analysis classification was used with the leave one out method. 38 normal and 48 abnormal (exudates, large drusens, fine drusens, choroidal neovascularization, central vein and artery occlusion, histoplasmosis, arteriosclerotic retinopathy, hemi-central retinal vein occlusion and more) were used and a specificity of 79% and sensitivity of 85.4% were achieved (the average classification rate is 82.2%). The success of the system can be accounted to the highly robust feature set which included translation, scale and semi-rotational, features. Additionally, this technique is database independent since the features were specifically tuned to the pathologies of the human eye.

Mathematics behind a Class of Image Restoration Algorithms

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Luminita STATE

2012-01-01

Full Text Available The restoration techniques are usually oriented toward modeling the type of degradation in order to infer the inverse process for recovering the given image. This approach usually involves the option for a criterion to numerically evaluate the quality of the resulted image and consequently the restoration process can be expressed in terms of an optimization problem. Most of the approaches are essentially based on additional hypothesis concerning the statistical properties of images. However, in real life applications, there is no enough information to support a certain particular image model, and consequently model-free developments have to be used instead. In our approaches the problem of image denoising/restoration is viewed as an information transmission/processing system, where the signal representing a certain clean image is transmitted through a noisy channel and only a noise-corrupted version is available. The aim is to recover the available signal as much as possible by using different noise removal techniques that is to build an accurate approximation of the initial image. Unfortunately, a series of image qualities, as for instance clarity, brightness, contrast, are affected by the noise removal techniques and consequently there is a need to partially restore them on the basis of information extracted exclusively from data. Following a brief description of the image restoration framework provided in the introductory part, a PCA-based methodology is presented in the second section of the paper. The basics of a new informational-based development for image restoration purposes and scatter matrix-based methods are given in the next two sections. The final section contains concluding remarks and suggestions for further work.

Joint Multi-Focus Fusion and Bayer ImageRestoration

Institute of Scientific and Technical Information of China (English)

Ling Guo; Bin Yang; Chao Yang

2015-01-01

In this paper, a joint multifocus image fusion and Bayer pattern image restoration algorithm for raw images of single-sensor colorimaging devices is proposed. Different from traditional fusion schemes, the raw Bayer pattern images are fused before colorrestoration. Therefore, the Bayer image restoration operation is only performed one time. Thus, the proposed algorithm is moreefficient than traditional fusion schemes. In detail, a clarity measurement of Bayer pattern image is defined for raw Bayer patternimages, and the fusion operator is performed on superpixels which provide powerful grouping cues of local image feature. Theraw images are merged with refined weight map to get the fused Bayer pattern image, which is restored by the demosaicingalgorithm to get the full resolution color image. Experimental results demonstrate that the proposed algorithm can obtain betterfused results with more natural appearance and fewer artifacts than the traditional algorithms.

Real-Time Imaging of Retinal Ganglion Cell Apoptosis

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Timothy E. Yap

2018-06-01

Full Text Available Monitoring real-time apoptosis in-vivo is an unmet need of neurodegeneration science, both in clinical and research settings. For patients, earlier diagnosis before the onset of symptoms provides a window of time in which to instigate treatment. For researchers, being able to objectively monitor the rates of underlying degenerative processes at a cellular level provides a biomarker with which to test novel therapeutics. The DARC (Detection of Apoptosing Retinal Cells project has developed a minimally invasive method using fluorescent annexin A5 to detect rates of apoptosis in retinal ganglion cells, the key pathological process in glaucoma. Numerous animal studies have used DARC to show efficacy of novel, pressure-independent treatment strategies in models of glaucoma and other conditions where retinal apoptosis is reported, including Alzheimer’s disease. This may forge exciting new links in the clinical science of treating both cognitive and visual decline. Human trials are now underway, successfully demonstrating the safety and efficacy of the technique to differentiate patients with progressive neurodegeneration from healthy individuals. We review the current perspectives on retinal ganglion cell apoptosis, the way in which this can be imaged, and the exciting advantages that these future methods hold in store.

Automatic detection of the macula in retinal fundus images using seeded mode tracking approach.

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Wong, Damon W K; Liu, Jiang; Tan, Ngan-Meng; Yin, Fengshou; Cheng, Xiangang; Cheng, Ching-Yu; Cheung, Gemmy C M; Wong, Tien Yin

2012-01-01

The macula is the part of the eye responsible for central high acuity vision. Detection of the macula is an important task in retinal image processing as a landmark for subsequent disease assessment, such as for age-related macula degeneration. In this paper, we have presented an approach to automatically determine the macula centre in retinal fundus images. First contextual information on the image is combined with a statistical model to obtain an approximate macula region of interest localization. Subsequently, we propose the use of a seeded mode tracking technique to locate the macula centre. The proposed approach is tested on a large dataset composed of 482 normal images and 162 glaucoma images from the ORIGA database and an additional 96 AMD images. The results show a ROI detection of 97.5%, and 90.5% correct detection of the macula within 1/3DD from a manual reference, which outperforms other current methods. The results are promising for the use of the proposed approach to locate the macula for the detection of macula diseases from retinal images.

Restoration of non-uniform exposure motion blurred image

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Luo, Yuanhong; Xu, Tingfa; Wang, Ningming; Liu, Feng

2014-11-01

Restoring motion-blurred image is the key technologies in the opto-electronic detection system. The imaging sensors such as CCD and infrared imaging sensor, which are mounted on the motion platforms, quickly move together with the platforms of high speed. As a result, the images become blur. The image degradation will cause great trouble for the succeeding jobs such as objects detection, target recognition and tracking. So the motion-blurred images must be restoration before detecting motion targets in the subsequent images. On the demand of the real weapon task, in order to deal with targets in the complex background, this dissertation uses the new theories in the field of image processing and computer vision to research the new technology of motion deblurring and motion detection. The principle content is as follows: 1) When the prior knowledge about degradation function is unknown, the uniform motion blurred images are restored. At first, the blur parameters, including the motion blur extent and direction of PSF(point spread function), are estimated individually in domain of logarithmic frequency. The direction of PSF is calculated by extracting the central light line of the spectrum, and the extent is computed by minimizing the correction between the fourier spectrum of the blurred image and a detecting function. Moreover, in order to remove the strip in the deblurred image, windows technique is employed in the algorithm, which makes the deblurred image clear. 2) According to the principle of infrared image non-uniform exposure, a new restoration model for infrared blurred images is developed. The fitting of infrared image non-uniform exposure curve is performed by experiment data. The blurred images are restored by the fitting curve.

Quality measures in applications of image restoration.

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Kriete, A; Naim, M; Schafer, L

2001-01-01

We describe a new method for the estimation of image quality in image restoration applications. We demonstrate this technique on a simulated data set of fluorescent beads, in comparison with restoration by three different deconvolution methods. Both the number of iterations and a regularisation factor are varied to enforce changes in the resulting image quality. First, the data sets are directly compared by an accuracy measure. These values serve to validate the image quality descriptor, which is developed on the basis of optical information theory. This most general measure takes into account the spectral energies and the noise, weighted in a logarithmic fashion. It is demonstrated that this method is particularly helpful as a user-oriented method to control the output of iterative image restorations and to eliminate the guesswork in choosing a suitable number of iterations.

Portable retinal imaging for eye disease screening using a consumer-grade digital camera

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Barriga, Simon; Larichev, Andrey; Zamora, Gilberto; Soliz, Peter

2012-03-01

The development of affordable means to image the retina is an important step toward the implementation of eye disease screening programs. In this paper we present the i-RxCam, a low-cost, hand-held, retinal camera for widespread applications such as tele-retinal screening for eye diseases like diabetic retinopathy (DR), glaucoma, and age-related ocular diseases. Existing portable retinal imagers do not meet the requirements of a low-cost camera with sufficient technical capabilities (field of view, image quality, portability, battery power, and ease-of-use) to be distributed widely to low volume clinics, such as the offices of single primary care physicians serving rural communities. The i-RxCam uses a Nikon D3100 digital camera body. The camera has a CMOS sensor with 14.8 million pixels. We use a 50mm focal lens that gives a retinal field of view of 45 degrees. The internal autofocus can compensate for about 2D (diopters) of focusing error. The light source is an LED produced by Philips with a linear emitting area that is transformed using a light pipe to the optimal shape at the eye pupil, an annulus. To eliminate corneal reflex we use a polarization technique in which the light passes through a nano-wire polarizer plate. This is a novel type of polarizer featuring high polarization separation (contrast ratio of more than 1000) and very large acceptance angle (>45 degrees). The i-RxCam approach will yield a significantly more economical retinal imaging device that would allow mass screening of the at-risk population.

Image degradation characteristics and restoration based on regularization for diffractive imaging

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Zhi, Xiyang; Jiang, Shikai; Zhang, Wei; Wang, Dawei; Li, Yun

2017-11-01

The diffractive membrane optical imaging system is an important development trend of ultra large aperture and lightweight space camera. However, related investigations on physics-based diffractive imaging degradation characteristics and corresponding image restoration methods are less studied. In this paper, the model of image quality degradation for the diffraction imaging system is first deduced mathematically based on diffraction theory and then the degradation characteristics are analyzed. On this basis, a novel regularization model of image restoration that contains multiple prior constraints is established. After that, the solving approach of the equation with the multi-norm coexistence and multi-regularization parameters (prior's parameters) is presented. Subsequently, the space-variant PSF image restoration method for large aperture diffractive imaging system is proposed combined with block idea of isoplanatic region. Experimentally, the proposed algorithm demonstrates its capacity to achieve multi-objective improvement including MTF enhancing, dispersion correcting, noise and artifact suppressing as well as image's detail preserving, and produce satisfactory visual quality. This can provide scientific basis for applications and possesses potential application prospects on future space applications of diffractive membrane imaging technology.

Retinal Vasculitis

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Rosenbaum, James T.; Sibley, Cailin H.; Lin, Phoebe

2016-01-01

Purpose of review Ophthalmologists and rheumatologists frequently miscommunicate in consulting on patients with retinal vasculitis. This report seeks to establish a common understanding of the term, retinal vasculitis, and to review recent papers on this diagnosis. Recent findings 1) The genetic basis of some rare forms of retinal vascular disease have recently been described. Identified genes include CAPN5, TREX1, and TNFAIP3; 2) Behçet’s disease is a systemic illness that is very commonly associated with occlusive retinal vasculitis; 3) retinal imaging including fluorescein angiography and other newer imaging modalities has proven crucial to the identification and characterization of retinal vasculitis and its complications; 4) although monoclonal antibodies to IL-17A or IL-1 beta failed in trials for Behçet’s disease, antibodies to TNF alpha, either infliximab or adalimumab, have demonstrated consistent benefit in managing this disease. Interferon treatment and B cell depletion therapy via rituximab may be beneficial in certain types of retinal vasculitis. Summary Retinal vasculitis is an important entity for rheumatologists to understand. Retinal vasculitis associated with Behçet’s disease responds to monoclonal antibodies that neutralize TNF, but the many other forms of non-infectious retinal vasculitis may require alternate therapeutic management. PMID:26945335

Intellectual system for images restoration

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Mardare, Igor

2005-02-01

Intelligence systems on basis of artificial neural networks and associative memory allow to solve effectively problems of recognition and restoration of images. However, within analytical technologies there are no dominating approaches of deciding of intellectual problems. Choice of the best technology depends on nature of problem, features of objects, volume of represented information about the object, number of classes of objects, etc. It is required to determine opportunities, preconditions and field of application of neural networks and associative memory for decision of problem of restoration of images and to use their supplementary benefits for further development of intelligence systems.

Textureless Macula Swelling Detection with Multiple Retinal Fundus Images

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Giancardo, Luca [ORNL; Meriaudeau, Fabrice [ORNL; Karnowski, Thomas Paul [ORNL; Tobin Jr, Kenneth William [ORNL; Grisan, Enrico [University of Padua, Padua, Italy; Favaro, Paolo [Heriot-Watt University, Edinburgh; Ruggeri, Alfredo [University of Padua, Padua, Italy; Chaum, Edward [University of Tennessee, Knoxville (UTK)

2010-01-01

Retinal fundus images acquired with non-mydriatic digital fundus cameras are a versatile tool for the diagnosis of various retinal diseases. Because of the ease of use of newer camera models and their relatively low cost, these cameras can be employed by operators with limited training for telemedicine or Point-of-Care applications. We propose a novel technique that uses uncalibrated multiple-view fundus images to analyse the swelling of the macula. This innovation enables the detection and quantitative measurement of swollen areas by remote ophthalmologists. This capability is not available with a single image and prone to error with stereo fundus cameras. We also present automatic algorithms to measure features from the reconstructed image which are useful in Point-of-Care automated diagnosis of early macular edema, e.g., before the appearance of exudation. The technique presented is divided into three parts: first, a preprocessing technique simultaneously enhances the dark microstructures of the macula and equalises the image; second, all available views are registered using non-morphological sparse features; finally, a dense pyramidal optical flow is calculated for all the images and statistically combined to build a naiveheight- map of the macula. Results are presented on three sets of synthetic images and two sets of real world images. These preliminary tests show the ability to infer a minimum swelling of 300 microns and to correlate the reconstruction with the swollen location.

Contrast-based sensorless adaptive optics for retinal imaging.

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Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T O; He, Zheng; Metha, Andrew

2015-09-01

Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes.

Congenital Simple Hamartoma of Retinal Pigment Epithelium: Clinical and Imaging Findings

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Mehmet Yasin Teke

2012-01-01

Full Text Available Congenital simple hamartoma of retinal pigment epithelium (CSHRPE is a rare, asymptomatic, and incidentally detected benign lesion. However, it is very important to do the differential diagnosis from other pigmented retinal lesions. Its clinical presentation and imaging findings are very helpful in doing this differentiation. This paper presents clinical and imaging findings of a 56-year-old woman with incidentally detected CSHRPE. The lesion was small, heavily pigmented, well circumscribed, and slightly elevated. Optical coherence tomography (OCT scanning was diagnostic and showed an elevated retina at the site of the lesion, increased optical reflectivity on its inner surface, optical shadowing of deeper structures, and clearly cut tumor margins. Ocular ultrasonography, fluorescein angiography, and fundus autofluorescence imaging which is firstly described in this report did not show any characteristic finding.

Reconstruction 3-dimensional image from 2-dimensional image of status optical coherence tomography (OCT) for analysis of changes in retinal thickness

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Arinilhaq,; Widita, Rena [Department of Physics, Nuclear Physics and Biophysics Research Group, Institut Teknologi Bandung (Indonesia)

2014-09-30

Optical Coherence Tomography is often used in medical image acquisition to diagnose that change due easy to use and low price. Unfortunately, this type of examination produces a two-dimensional retinal image of the point of acquisition. Therefore, this study developed a method that combines and reconstruct 2-dimensional retinal images into three-dimensional images to display volumetric macular accurately. The system is built with three main stages: data acquisition, data extraction and 3-dimensional reconstruction. At data acquisition step, Optical Coherence Tomography produced six *.jpg images of each patient were further extracted with MATLAB 2010a software into six one-dimensional arrays. The six arrays are combined into a 3-dimensional matrix using a kriging interpolation method with SURFER9 resulting 3-dimensional graphics of macula. Finally, system provides three-dimensional color graphs based on the data distribution normal macula. The reconstruction system which has been designed produces three-dimensional images with size of 481 × 481 × h (retinal thickness) pixels.

Adaptive optics fundus images of cone photoreceptors in the macula of patients with retinitis pigmentosa.

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Tojo, Naoki; Nakamura, Tomoko; Fuchizawa, Chiharu; Oiwake, Toshihiko; Hayashi, Atsushi

2013-01-01

The purpose of this study was to examine cone photoreceptors in the macula of patients with retinitis pigmentosa using an adaptive optics fundus camera and to investigate any correlations between cone photoreceptor density and findings on optical coherence tomography and fundus autofluorescence. We examined two patients with typical retinitis pigmentosa who underwent ophthalmological examination, including measurement of visual acuity, and gathering of electroretinographic, optical coherence tomographic, fundus autofluorescent, and adaptive optics fundus images. The cone photoreceptors in the adaptive optics images of the two patients with retinitis pigmentosa and five healthy subjects were analyzed. An abnormal parafoveal ring of high-density fundus autofluorescence was observed in the macula in both patients. The border of the ring corresponded to the border of the external limiting membrane and the inner segment and outer segment line in the optical coherence tomographic images. Cone photoreceptors at the abnormal parafoveal ring were blurred and decreased in the adaptive optics images. The blurred area corresponded to the abnormal parafoveal ring in the fundus autofluorescence images. Cone densities were low at the blurred areas and at the nasal and temporal retina along a line from the fovea compared with those of healthy controls. The results for cone spacing and Voronoi domains in the macula corresponded with those for the cone densities. Cone densities were heavily decreased in the macula, especially at the parafoveal ring on high-density fundus autofluorescence in both patients with retinitis pigmentosa. Adaptive optics images enabled us to observe in vivo changes in the cone photoreceptors of patients with retinitis pigmentosa, which corresponded to changes in the optical coherence tomographic and fundus autofluorescence images.

Adaptive optics fundus images of cone photoreceptors in the macula of patients with retinitis pigmentosa

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Tojo N

2013-01-01

Full Text Available Naoki Tojo, Tomoko Nakamura, Chiharu Fuchizawa, Toshihiko Oiwake, Atsushi HayashiDepartment of Ophthalmology, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, JapanBackground: The purpose of this study was to examine cone photoreceptors in the macula of patients with retinitis pigmentosa using an adaptive optics fundus camera and to investigate any correlations between cone photoreceptor density and findings on optical coherence tomography and fundus autofluorescence.Methods: We examined two patients with typical retinitis pigmentosa who underwent ophthalmological examination, including measurement of visual acuity, and gathering of electroretinographic, optical coherence tomographic, fundus autofluorescent, and adaptive optics fundus images. The cone photoreceptors in the adaptive optics images of the two patients with retinitis pigmentosa and five healthy subjects were analyzed.Results: An abnormal parafoveal ring of high-density fundus autofluorescence was observed in the macula in both patients. The border of the ring corresponded to the border of the external limiting membrane and the inner segment and outer segment line in the optical coherence tomographic images. Cone photoreceptors at the abnormal parafoveal ring were blurred and decreased in the adaptive optics images. The blurred area corresponded to the abnormal parafoveal ring in the fundus autofluorescence images. Cone densities were low at the blurred areas and at the nasal and temporal retina along a line from the fovea compared with those of healthy controls. The results for cone spacing and Voronoi domains in the macula corresponded with those for the cone densities.Conclusion: Cone densities were heavily decreased in the macula, especially at the parafoveal ring on high-density fundus autofluorescence in both patients with retinitis pigmentosa. Adaptive optics images enabled us to observe in vivo changes in the cone photoreceptors of

A new approach to optic disc detection in human retinal images using the firefly algorithm.

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Rahebi, Javad; Hardalaç, Fırat

2016-03-01

There are various methods and algorithms to detect the optic discs in retinal images. In recent years, much attention has been given to the utilization of the intelligent algorithms. In this paper, we present a new automated method of optic disc detection in human retinal images using the firefly algorithm. The firefly intelligent algorithm is an emerging intelligent algorithm that was inspired by the social behavior of fireflies. The population in this algorithm includes the fireflies, each of which has a specific rate of lighting or fitness. In this method, the insects are compared two by two, and the less attractive insects can be observed to move toward the more attractive insects. Finally, one of the insects is selected as the most attractive, and this insect presents the optimum response to the problem in question. Here, we used the light intensity of the pixels of the retinal image pixels instead of firefly lightings. The movement of these insects due to local fluctuations produces different light intensity values in the images. Because the optic disc is the brightest area in the retinal images, all of the insects move toward brightest area and thus specify the location of the optic disc in the image. The results of implementation show that proposed algorithm could acquire an accuracy rate of 100 % in DRIVE dataset, 95 % in STARE dataset, and 94.38 % in DiaRetDB1 dataset. The results of implementation reveal high capability and accuracy of proposed algorithm in the detection of the optic disc from retinal images. Also, recorded required time for the detection of the optic disc in these images is 2.13 s for DRIVE dataset, 2.81 s for STARE dataset, and 3.52 s for DiaRetDB1 dataset accordingly. These time values are average value.

Retinal Imaging of Infants on Spectral Domain Optical Coherence Tomography

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Anand Vinekar

2015-01-01

Full Text Available Spectral domain coherence tomography (SD OCT has become an important tool in the management of pediatric retinal diseases. It is a noncontact imaging device that provides detailed assessment of the microanatomy and pathology of the infant retina with a short acquisition time allowing office examination without the requirement of anesthesia. Our understanding of the development and maturation of the infant fovea has been enhanced by SD OCT allowing an in vivo assessment that correlates with histopathology. This has helped us understand the critical correlation of foveal development with visual potential in the first year of life and beyond. In this review, we summarize the recent literature on the clinical applications of SD OCT in studying the pathoanatomy of the infant macula, its ability to detect subclinical features, and its correlation with disease and vision. Retinopathy of prematurity and macular edema have been discussed in detail. The review also summarizes the current status of SD OCT in other infant retinal conditions, imaging the optic nerve, the choroid, and the retinal nerve fibre in infants and children, and suggests future areas of research.

Restoration for Noise Removal in Quantum Images

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Liu, Kai; Zhang, Yi; Lu, Kai; Wang, Xiaoping

2017-09-01

Quantum computation has become increasingly attractive in the past few decades due to its extraordinary performance. As a result, some studies focusing on image representation and processing via quantum mechanics have been done. However, few of them have considered the quantum operations for images restoration. To address this problem, three noise removal algorithms are proposed in this paper based on the novel enhanced quantum representation model, oriented to two kinds of noise pollution (Salt-and-Pepper noise and Gaussian noise). For the first algorithm Q-Mean, it is designed to remove the Salt-and-Pepper noise. The noise points are extracted through comparisons with the adjacent pixel values, after which the restoration operation is finished by mean filtering. As for the second method Q-Gauss, a special mask is applied to weaken the Gaussian noise pollution. The third algorithm Q-Adapt is effective for the source image containing unknown noise. The type of noise can be judged through the quantum statistic operations for the color value of the whole image, and then different noise removal algorithms are used to conduct image restoration respectively. Performance analysis reveals that our methods can offer high restoration quality and achieve significant speedup through inherent parallelism of quantum computation.

Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

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Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

2010-02-01

Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

Small-kernel constrained-least-squares restoration of sampled image data

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Hazra, Rajeeb; Park, Stephen K.

1992-10-01

Constrained least-squares image restoration, first proposed by Hunt twenty years ago, is a linear image restoration technique in which the restoration filter is derived by maximizing the smoothness of the restored image while satisfying a fidelity constraint related to how well the restored image matches the actual data. The traditional derivation and implementation of the constrained least-squares restoration filter is based on an incomplete discrete/discrete system model which does not account for the effects of spatial sampling and image reconstruction. For many imaging systems, these effects are significant and should not be ignored. In a recent paper Park demonstrated that a derivation of the Wiener filter based on the incomplete discrete/discrete model can be extended to a more comprehensive end-to-end, continuous/discrete/continuous model. In a similar way, in this paper, we show that a derivation of the constrained least-squares filter based on the discrete/discrete model can also be extended to this more comprehensive continuous/discrete/continuous model and, by so doing, an improved restoration filter is derived. Building on previous work by Reichenbach and Park for the Wiener filter, we also show that this improved constrained least-squares restoration filter can be efficiently implemented as a small-kernel convolution in the spatial domain.

Restoration of color in a remote sensing image and its quality evaluation

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Zhang, Zuxun; Li, Zhijiang; Zhang, Jianqing; Wang, Zhihe

2003-09-01

This paper is focused on the restoration of color remote sensing (including airborne photo). A complete approach is recommended. It propose that two main aspects should be concerned in restoring a remote sensing image, that are restoration of space information, restoration of photometric information. In this proposal, the restoration of space information can be performed by making the modulation transfer function (MTF) as degradation function, in which the MTF is obtained by measuring the edge curve of origin image. The restoration of photometric information can be performed by improved local maximum entropy algorithm. What's more, a valid approach in processing color remote sensing image is recommended. That is splits the color remote sensing image into three monochromatic images which corresponding three visible light bands and synthesizes the three images after being processed separately with psychological color vision restriction. Finally, three novel evaluation variables are obtained based on image restoration to evaluate the image restoration quality in space restoration quality and photometric restoration quality. An evaluation is provided at last.

Nanowire arrays restore vision in blind mice.

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Tang, Jing; Qin, Nan; Chong, Yan; Diao, Yupu; Yiliguma; Wang, Zhexuan; Xue, Tian; Jiang, Min; Zhang, Jiayi; Zheng, Gengfeng

2018-03-06

The restoration of light response with complex spatiotemporal features in retinal degenerative diseases towards retinal prosthesis has proven to be a considerable challenge over the past decades. Herein, inspired by the structure and function of photoreceptors in retinas, we develop artificial photoreceptors based on gold nanoparticle-decorated titania nanowire arrays, for restoration of visual responses in the blind mice with degenerated photoreceptors. Green, blue and near UV light responses in the retinal ganglion cells (RGCs) are restored with a spatial resolution better than 100 µm. ON responses in RGCs are blocked by glutamatergic antagonists, suggesting functional preservation of the remaining retinal circuits. Moreover, neurons in the primary visual cortex respond to light after subretinal implant of nanowire arrays. Improvement in pupillary light reflex suggests the behavioral recovery of light sensitivity. Our study will shed light on the development of a new generation of optoelectronic toolkits for subretinal prosthetic devices.

Quantitative Image Restoration in Bright Field Optical Microscopy.

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Gutiérrez-Medina, Braulio; Sánchez Miranda, Manuel de Jesús

2017-11-07

Bright field (BF) optical microscopy is regarded as a poor method to observe unstained biological samples due to intrinsic low image contrast. We introduce quantitative image restoration in bright field (QRBF), a digital image processing method that restores out-of-focus BF images of unstained cells. Our procedure is based on deconvolution, using a point spread function modeled from theory. By comparing with reference images of bacteria observed in fluorescence, we show that QRBF faithfully recovers shape and enables quantify size of individual cells, even from a single input image. We applied QRBF in a high-throughput image cytometer to assess shape changes in Escherichia coli during hyperosmotic shock, finding size heterogeneity. We demonstrate that QRBF is also applicable to eukaryotic cells (yeast). Altogether, digital restoration emerges as a straightforward alternative to methods designed to generate contrast in BF imaging for quantitative analysis. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Automatic detection of diabetic retinopathy features in ultra-wide field retinal images

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Levenkova, Anastasia; Sowmya, Arcot; Kalloniatis, Michael; Ly, Angelica; Ho, Arthur

2017-03-01

Diabetic retinopathy (DR) is a major cause of irreversible vision loss. DR screening relies on retinal clinical signs (features). Opportunities for computer-aided DR feature detection have emerged with the development of Ultra-WideField (UWF) digital scanning laser technology. UWF imaging covers 82% greater retinal area (200°), against 45° in conventional cameras3 , allowing more clinically relevant retinopathy to be detected4 . UWF images also provide a high resolution of 3078 x 2702 pixels. Currently DR screening uses 7 overlapping conventional fundus images, and the UWF images provide similar results1,4. However, in 40% of cases, more retinopathy was found outside the 7-field ETDRS) fields by UWF and in 10% of cases, retinopathy was reclassified as more severe4 . This is because UWF imaging allows examination of both the central retina and more peripheral regions, with the latter implicated in DR6 . We have developed an algorithm for automatic recognition of DR features, including bright (cotton wool spots and exudates) and dark lesions (microaneurysms and blot, dot and flame haemorrhages) in UWF images. The algorithm extracts features from grayscale (green "red-free" laser light) and colour-composite UWF images, including intensity, Histogram-of-Gradient and Local binary patterns. Pixel-based classification is performed with three different classifiers. The main contribution is the automatic detection of DR features in the peripheral retina. The method is evaluated by leave-one-out cross-validation on 25 UWF retinal images with 167 bright lesions, and 61 other images with 1089 dark lesions. The SVM classifier performs best with AUC of 94.4% / 95.31% for bright / dark lesions.

Chaetomium retinitis.

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Tabbara, Khalid F; Wedin, Keith; Al Haddab, Saad

2010-01-01

To report a case of Chaetomium atrobrunneum retinitis in a patient with Hodgkin lymphoma. We studied the ocular manifestations of an 11-year-old boy with retinitis. Biomicroscopy, ophthalmoscopy, and fundus photography were done. Magnetic resonance imaging of the brain was performed. A vitreous biopsy was subjected to viral, bacterial, and fungal cultures. Vitreous culture grew C. atrobrunneum. Magnetic resonance imaging showed multiple cerebral lesions consistent with an infectious process. The patient was given intravenous voriconazole and showed improvement of the ocular and central nervous system lesions. We report a case of central nervous system and ocular lesions by C. atrobrunneum. The retinitis was initially misdiagnosed as cytomegaloviral retinitis. Vitreous biopsy helped in the early diagnosis and prompt treatment of a life- and vision-threatening infection.

Personal identification based on blood vessels of retinal fundus images

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Fukuta, Keisuke; Nakagawa, Toshiaki; Hayashi, Yoshinori; Hatanaka, Yuji; Hara, Takeshi; Fujita, Hiroshi

2008-03-01

Biometric technique has been implemented instead of conventional identification methods such as password in computer, automatic teller machine (ATM), and entrance and exit management system. We propose a personal identification (PI) system using color retinal fundus images which are unique to each individual. The proposed procedure for identification is based on comparison of an input fundus image with reference fundus images in the database. In the first step, registration between the input image and the reference image is performed. The step includes translational and rotational movement. The PI is based on the measure of similarity between blood vessel images generated from the input and reference images. The similarity measure is defined as the cross-correlation coefficient calculated from the pixel values. When the similarity is greater than a predetermined threshold, the input image is identified. This means both the input and the reference images are associated to the same person. Four hundred sixty-two fundus images including forty-one same-person's image pairs were used for the estimation of the proposed technique. The false rejection rate and the false acceptance rate were 9.9×10 -5% and 4.3×10 -5%, respectively. The results indicate that the proposed method has a higher performance than other biometrics except for DNA. To be used for practical application in the public, the device which can take retinal fundus images easily is needed. The proposed method is applied to not only the PI but also the system which warns about misfiling of fundus images in medical facilities.

Vessel Segmentation in Retinal Images Using Multi-scale Line Operator and K-Means Clustering.

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Saffarzadeh, Vahid Mohammadi; Osareh, Alireza; Shadgar, Bita

2014-04-01

Detecting blood vessels is a vital task in retinal image analysis. The task is more challenging with the presence of bright and dark lesions in retinal images. Here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. First, the negative impact of bright lesions is reduced by using K-means segmentation in a perceptive space. Then, a multi-scale line operator is utilized to detect vessels while ignoring some of the dark lesions, which have intensity structures different from the line-shaped vessels in the retina. The proposed algorithm is tested on two publicly available STARE and DRIVE databases. The performance of the method is measured by calculating the area under the receiver operating characteristic curve and the segmentation accuracy. The proposed method achieves 0.9483 and 0.9387 localization accuracy against STARE and DRIVE respectively.

Multimodal imaging of small hard retinal drusen in young healthy adults

DEFF Research Database (Denmark)

Pedersen, Hilde R; Gilson, Stuart J; Dubra, Alfredo

2018-01-01

BACKGROUND: Small hard macular drusen can be observed in the retina of adults as young as 18 years of age. Here, we seek to describe the in vivo topography and geometry of these drusen. METHODS: Retinal images were acquired in young, healthy adults using colour fundus photography, spectral domain...... the foveal centre were characterised. RESULTS: Small hard drusen were seen on colour photographs in 21 out of 97 participants and 26 drusen in 12 eyes in 11 participants were imaged using the full protocol. Drusen were easily identifiable in all modalities, except a few very small ones, which were...... not visible on SD-OCT. On AOSLO images, these drusen appeared as round, oval or lobular areas (up to three lobules) of diameter 22-61 µm where cone photoreceptor reflectivity and density was decreased (p=0.049). This was usually associated with discrete thickening of the retinal pigment epithelium (RPE...

Comparison of conventional color fundus photography and multicolor imaging in choroidal or retinal lesions.

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Muftuoglu, Ilkay Kilic; Gaber, Raouf; Bartsch, Dirk-Uwe; Meshi, Amit; Goldbaum, Michael; Freeman, William R

2018-04-01

Our purpose was to compare the characteristics of the retinal and choroidal lesions including choroidal nevus, choroidal melanoma and congenital hypertrophy of the retina pigment epithelium using conventional color fundus photography (CFP) and multicolor imaging (MCI). The paired images of patients with retinal or choroidal lesions were assessed for the visibility of lesion's border, halo and drusen using a grading scale (0-2). The area of the lesion was measured on both imaging modalities. The same grading was also done on the individual color channels of MCI for a further evaluation. Thirty-three eyes of 33 patients were included. There were no significant differences in the mean border, drusen and halo visibility scores between the two imaging modalities (p = 0.12, p = 0.70, p = 0.35). However, the mean area of the lesion was significantly smaller on MCI than that on CFP (14.9±3.3 versus 18.7±3.4 mm 2 , p = 0.01). The appearance of choroidal and/ or retinal lesions on MCI may be different than that on CFP. Though MCI can provide similar information with CFP for the features of retinal and/ or choroidal lesions including border, halo and drusen; the infrared light reflection on MCI underestimates the extent of the choroidal lesion by 33%.

Image restoration and processing methods

International Nuclear Information System (INIS)

Daniell, G.J.

1984-01-01

This review will stress the importance of using image restoration techniques that deal with incomplete, inconsistent, and noisy data and do not introduce spurious features into the processed image. No single image is equally suitable for both the resolution of detail and the accurate measurement of intensities. A good general purpose technique is the maximum entropy method and the basis and use of this will be explained. (orig.)

Improving high resolution retinal image quality using speckle illumination HiLo imaging.

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Zhou, Xiaolin; Bedggood, Phillip; Metha, Andrew

2014-08-01

Retinal image quality from flood illumination adaptive optics (AO) ophthalmoscopes is adversely affected by out-of-focus light scatter due to the lack of confocality. This effect is more pronounced in small eyes, such as that of rodents, because the requisite high optical power confers a large dioptric thickness to the retina. A recently-developed structured illumination microscopy (SIM) technique called HiLo imaging has been shown to reduce the effect of out-of-focus light scatter in flood illumination microscopes and produce pseudo-confocal images with significantly improved image quality. In this work, we adopted the HiLo technique to a flood AO ophthalmoscope and performed AO imaging in both (physical) model and live rat eyes. The improvement in image quality from HiLo imaging is shown both qualitatively and quantitatively by using spatial spectral analysis.

Real-time image restoration for iris recognition systems.

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Kang, Byung Jun; Park, Kang Ryoung

2007-12-01

In the field of biometrics, it has been reported that iris recognition techniques have shown high levels of accuracy because unique patterns of the human iris, which has very many degrees of freedom, are used. However, because conventional iris cameras have small depth-of-field (DOF) areas, input iris images can easily be blurred, which can lead to lower recognition performance, since iris patterns are transformed by the blurring caused by optical defocusing. To overcome these problems, an autofocusing camera can be used. However, this inevitably increases the cost, size, and complexity of the system. Therefore, we propose a new real-time iris image-restoration method, which can increase the camera's DOF without requiring any additional hardware. This paper presents five novelties as compared to previous works: 1) by excluding eyelash and eyelid regions, it is possible to obtain more accurate focus scores from input iris images; 2) the parameter of the point spread function (PSF) can be estimated in terms of camera optics and measured focus scores; therefore, parameter estimation is more accurate than it has been in previous research; 3) because the PSF parameter can be obtained by using a predetermined equation, iris image restoration can be done in real-time; 4) by using a constrained least square (CLS) restoration filter that considers noise, performance can be greatly enhanced; and 5) restoration accuracy can also be enhanced by estimating the weight value of the noise-regularization term of the CLS filter according to the amount of image blurring. Experimental results showed that iris recognition errors when using the proposed restoration method were greatly reduced as compared to those results achieved without restoration or those achieved using previous iris-restoration methods.

Automated detection of diabetic retinopathy in retinal images

Directory of Open Access Journals (Sweden)

Carmen Valverde

2016-01-01

Full Text Available Diabetic retinopathy (DR is a disease with an increasing prevalence and the main cause of blindness among working-age population. The risk of severe vision loss can be significantly reduced by timely diagnosis and treatment. Systematic screening for DR has been identified as a cost-effective way to save health services resources. Automatic retinal image analysis is emerging as an important screening tool for early DR detection, which can reduce the workload associated to manual grading as well as save diagnosis costs and time. Many research efforts in the last years have been devoted to developing automatic tools to help in the detection and evaluation of DR lesions. However, there is a large variability in the databases and evaluation criteria used in the literature, which hampers a direct comparison of the different studies. This work is aimed at summarizing the results of the available algorithms for the detection and classification of DR pathology. A detailed literature search was conducted using PubMed. Selected relevant studies in the last 10 years were scrutinized and included in the review. Furthermore, we will try to give an overview of the available commercial software for automatic retinal image analysis.

Automated detection of diabetic retinopathy in retinal images.

Science.gov (United States)

Valverde, Carmen; Garcia, Maria; Hornero, Roberto; Lopez-Galvez, Maria I

2016-01-01

Diabetic retinopathy (DR) is a disease with an increasing prevalence and the main cause of blindness among working-age population. The risk of severe vision loss can be significantly reduced by timely diagnosis and treatment. Systematic screening for DR has been identified as a cost-effective way to save health services resources. Automatic retinal image analysis is emerging as an important screening tool for early DR detection, which can reduce the workload associated to manual grading as well as save diagnosis costs and time. Many research efforts in the last years have been devoted to developing automatic tools to help in the detection and evaluation of DR lesions. However, there is a large variability in the databases and evaluation criteria used in the literature, which hampers a direct comparison of the different studies. This work is aimed at summarizing the results of the available algorithms for the detection and classification of DR pathology. A detailed literature search was conducted using PubMed. Selected relevant studies in the last 10 years were scrutinized and included in the review. Furthermore, we will try to give an overview of the available commercial software for automatic retinal image analysis.

In-vivo imaging of retinal nerve fiber layer vasculature: imaging – histology comparison

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Libby Richard T

2009-08-01

Full Text Available Abstract Background Although it has been suggested that alterations of nerve fiber layer vasculature may be involved in the etiology of eye diseases, including glaucoma, it has not been possible to examine this vasculature in-vivo. This report describes a novel imaging method, fluorescence adaptive optics (FAO scanning laser ophthalmoscopy (SLO, that makes possible for the first time in-vivo imaging of this vasculature in the living macaque, comparing in-vivo and ex-vivo imaging of this vascular bed. Methods We injected sodium fluorescein intravenously in two macaque monkeys while imaging the retina with an FAO-SLO. An argon laser provided the 488 nm excitation source for fluorescence imaging. Reflectance images, obtained simultaneously with near infrared light, permitted precise surface registration of individual frames of the fluorescence imaging. In-vivo imaging was then compared to ex-vivo confocal microscopy of the same tissue. Results Superficial focus (innermost retina at all depths within the NFL revealed a vasculature with extremely long capillaries, thin walls, little variation in caliber and parallel-linked structure oriented parallel to the NFL axons, typical of the radial peripapillary capillaries (RPCs. However, at a deeper focus beneath the NFL, (toward outer retina the polygonal pattern typical of the ganglion cell layer (inner and outer retinal vasculature was seen. These distinguishing patterns were also seen on histological examination of the same retinas. Furthermore, the thickness of the RPC beds and the caliber of individual RPCs determined by imaging closely matched that measured in histological sections. Conclusion This robust method demonstrates in-vivo, high-resolution, confocal imaging of the vasculature through the full thickness of the NFL in the living macaque, in precise agreement with histology. FAO provides a new tool to examine possible primary or secondary role of the nerve fiber layer vasculature in retinal

Image restoration from non-uniform magnetic field influence for direct Fourier NMR imaging

International Nuclear Information System (INIS)

Sekihara, K.; Kuroda, M.; Kohno, H.

1984-01-01

A new technique is proposed for NMR image restoration from the influence of main magnetic field non-uniformities. This technique is applicable to direct Fourier NMR imaging. The mathematical basis and details of this technique are fully described. Modification to include image restoration from non-linear field gradient influence is also presented. Computer simulation demonstrates the effectiveness of this technique for both Fourier zeugmatography and spin-warp imaging. (author)

Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images.

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Elad, M; Feuer, A

1997-01-01

The three main tools in the single image restoration theory are the maximum likelihood (ML) estimator, the maximum a posteriori probability (MAP) estimator, and the set theoretic approach using projection onto convex sets (POCS). This paper utilizes the above known tools to propose a unified methodology toward the more complicated problem of superresolution restoration. In the superresolution restoration problem, an improved resolution image is restored from several geometrically warped, blurred, noisy and downsampled measured images. The superresolution restoration problem is modeled and analyzed from the ML, the MAP, and POCS points of view, yielding a generalization of the known superresolution restoration methods. The proposed restoration approach is general but assumes explicit knowledge of the linear space- and time-variant blur, the (additive Gaussian) noise, the different measured resolutions, and the (smooth) motion characteristics. A hybrid method combining the simplicity of the ML and the incorporation of nonellipsoid constraints is presented, giving improved restoration performance, compared with the ML and the POCS approaches. The hybrid method is shown to converge to the unique optimal solution of a new definition of the optimization problem. Superresolution restoration from motionless measurements is also discussed. Simulations demonstrate the power of the proposed methodology.

Polarization sensitive optical coherence tomography at 1060 nm for retinal imaging

International Nuclear Information System (INIS)

Torzicky, T.

2014-01-01

The aim of this thesis was to develop a Polarization Sensitive Optical Coherence Tomography (PS-OCT) device for ocular imaging in the 1 µm wavelength range and to explore its capabilities to image healthy subjects and patients with various retinal disorders. PS-OCT set-ups working in the 840 nm range have been used in several clinical studies, for examining different retinal pathologies. Especially the segmentation of the retinal pigment epithelium (RPE) based on PS-OCT data shows advantages in cases of age related macular degeneration (AMD) in comparison to segmentation based on intensity images from commercial OCT systems. OCT imaging in the 1 µm wavelength region has recently gained popularity for ophthalmic applications due to the fact that it is perfectly suitable for enhanced visualization of choroid and sclera. This is due to decreased scattering and absorption in the RPE with increasing wavelength and due to the local absorption minimum of water (the vitreous of the eye consists mainly of water) for wavelengths around 1060 nm. An additional advantage is that a higher imaging quality in patients with corneal haze or cataract can be achieved when using OCT systems working at 1 µm. In this work we combine the advantages of PS-OCT imaging with the enhanced penetration depth of the 1 µm wavelength range for acquiring intensity, retardation, axis orientation and degree of polarization uniformity (DOPU) images of choroid and sclera. As a first step different PS-OCT set-ups working at 1060 nm were developed and a comparison regarding set-up parameters and imaging performance was accomplished. The two different set-ups that were built and investigated were a spectrometer based Fourier Domain OCT set-up and a swept source Fourier Domain OCT set-up. The swept source set-up was tested with two different light sources, a commercially available swept source laser (A-Scan rate of 100 kHz) and a prototype of a Fourier Domain Mode Locked (FDML) laser (A-Scan rate of 350

Low dose CT image restoration using a database of image patches

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Ha, Sungsoo; Mueller, Klaus

2015-01-01

Reducing the radiation dose in CT imaging has become an active research topic and many solutions have been proposed to remove the significant noise and streak artifacts in the reconstructed images. Most of these methods operate within the domain of the image that is subject to restoration. This, however, poses limitations on the extent of filtering possible. We advocate to take into consideration the vast body of external knowledge that exists in the domain of already acquired medical CT images, since after all, this is what radiologists do when they examine these low quality images. We can incorporate this knowledge by creating a database of prior scans, either of the same patient or a diverse corpus of different patients, to assist in the restoration process. Our paper follows up on our previous work that used a database of images. Using images, however, is challenging since it requires tedious and error prone registration and alignment. Our new method eliminates these problems by storing a diverse set of small image patches in conjunction with a localized similarity matching scheme. We also empirically show that it is sufficient to store these patches without anatomical tags since their statistics are sufficiently strong to yield good similarity matches from the database and as a direct effect, produce image restorations of high quality. A final experiment demonstrates that our global database approach can recover image features that are difficult to preserve with conventional denoising approaches.

Mixture model-based clustering and logistic regression for automatic detection of microaneurysms in retinal images

Science.gov (United States)

Sánchez, Clara I.; Hornero, Roberto; Mayo, Agustín; García, María

2009-02-01

Diabetic Retinopathy is one of the leading causes of blindness and vision defects in developed countries. An early detection and diagnosis is crucial to avoid visual complication. Microaneurysms are the first ocular signs of the presence of this ocular disease. Their detection is of paramount importance for the development of a computer-aided diagnosis technique which permits a prompt diagnosis of the disease. However, the detection of microaneurysms in retinal images is a difficult task due to the wide variability that these images usually present in screening programs. We propose a statistical approach based on mixture model-based clustering and logistic regression which is robust to the changes in the appearance of retinal fundus images. The method is evaluated on the public database proposed by the Retinal Online Challenge in order to obtain an objective performance measure and to allow a comparative study with other proposed algorithms.

Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques

Directory of Open Access Journals (Sweden)

Kemal Akyol

2016-01-01

Full Text Available With the advances in the computer field, methods and techniques in automatic image processing and analysis provide the opportunity to detect automatically the change and degeneration in retinal images. Localization of the optic disc is extremely important for determining the hard exudate lesions or neovascularization, which is the later phase of diabetic retinopathy, in computer aided eye disease diagnosis systems. Whereas optic disc detection is fairly an easy process in normal retinal images, detecting this region in the retinal image which is diabetic retinopathy disease may be difficult. Sometimes information related to optic disc and hard exudate information may be the same in terms of machine learning. We presented a novel approach for efficient and accurate localization of optic disc in retinal images having noise and other lesions. This approach is comprised of five main steps which are image processing, keypoint extraction, texture analysis, visual dictionary, and classifier techniques. We tested our proposed technique on 3 public datasets and obtained quantitative results. Experimental results show that an average optic disc detection accuracy of 94.38%, 95.00%, and 90.00% is achieved, respectively, on the following public datasets: DIARETDB1, DRIVE, and ROC.

Fast vessel segmentation in retinal images using multi-scale enhancement and second-order local entropy

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Yu, H.; Barriga, S.; Agurto, C.; Zamora, G.; Bauman, W.; Soliz, P.

2012-03-01

Retinal vasculature is one of the most important anatomical structures in digital retinal photographs. Accurate segmentation of retinal blood vessels is an essential task in automated analysis of retinopathy. This paper presents a new and effective vessel segmentation algorithm that features computational simplicity and fast implementation. This method uses morphological pre-processing to decrease the disturbance of bright structures and lesions before vessel extraction. Next, a vessel probability map is generated by computing the eigenvalues of the second derivatives of Gaussian filtered image at multiple scales. Then, the second order local entropy thresholding is applied to segment the vessel map. Lastly, a rule-based decision step, which measures the geometric shape difference between vessels and lesions is applied to reduce false positives. The algorithm is evaluated on the low-resolution DRIVE and STARE databases and the publicly available high-resolution image database from Friedrich-Alexander University Erlangen-Nuremberg, Germany). The proposed method achieved comparable performance to state of the art unsupervised vessel segmentation methods with a competitive faster speed on the DRIVE and STARE databases. For the high resolution fundus image database, the proposed algorithm outperforms an existing approach both on performance and speed. The efficiency and robustness make the blood vessel segmentation method described here suitable for broad application in automated analysis of retinal images.

Localized Retinal Nerve Fiber Layer Defects in Red-free Photographs Versus En Face Structural Optical Coherence Tomography Images.

Science.gov (United States)

Jung, Jae Hoon; Park, Ji-Hye; Yoo, Chungkwon; Kim, Yong Yeon

2018-03-01

The purpose of this article is to compare the locations of localized retinal nerve fiber layer (RNFL) defects in red-free fundus photographs and optical coherence tomography (OCT) en face images. We performed a retrospective, comparative study on 46 eyes from 46 glaucoma patients with localized RNFL defects observed in red-free fundus photographs. En face structural images were obtained in the superficial and whole retinal layers using OCT and were overlaid on the corresponding red-free fundus photographs. The proximal/distal angular locations and angular width of each RNFL defect in red-free photos (red-free defects) and in en face structural images (en face defects) were compared. In the superficial retinal layer, there were no significant differences between red-free and en face defects on the proximal/distal angular location and angular width. In the whole retinal layer, the degree of the distal angular location of the en face defects was significantly larger than that of the red-free defects (71.85±18.26 vs. 70.87±17.90 degrees, P=0.003). The correlations of clinical variables with the differences in angular parameters between red-free and en face defects were not significant in the superficial retinal layer. The average RNFL thickness was negatively correlated with the difference in the distal angular location in the whole retinal layer (Pearson correlation coefficient=-0.401, P=0.006). Localized RNFL defects detected in OCT en face structural images of the superficial retinal layer showed high topographic correlation with defects detected in red-free photographs. OCT en face structural images in the superficial layer may be an alternative to red-free fundus photography for the identification of localized RNFL defects in glaucomatous eyes.

Restoration and Enhancement of Underwater Images Based on Bright Channel Prior

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Yakun Gao

2016-01-01

Full Text Available This paper proposed a new method of underwater images restoration and enhancement which was inspired by the dark channel prior in image dehazing field. Firstly, we proposed the bright channel prior of underwater environment. By estimating and rectifying the bright channel image, estimating the atmospheric light, and estimating and refining the transmittance image, eventually underwater images were restored. Secondly, in order to rectify the color distortion, the restoration images were equalized by using the deduced histogram equalization. The experiment results showed that the proposed method could enhance the quality of underwater images effectively.

Supervised retinal vessel segmentation from color fundus images based on matched filtering and AdaBoost classifier.

Directory of Open Access Journals (Sweden)

Nogol Memari

Full Text Available The structure and appearance of the blood vessel network in retinal fundus images is an essential part of diagnosing various problems associated with the eyes, such as diabetes and hypertension. In this paper, an automatic retinal vessel segmentation method utilizing matched filter techniques coupled with an AdaBoost classifier is proposed. The fundus image is enhanced using morphological operations, the contrast is increased using contrast limited adaptive histogram equalization (CLAHE method and the inhomogeneity is corrected using Retinex approach. Then, the blood vessels are enhanced using a combination of B-COSFIRE and Frangi matched filters. From this preprocessed image, different statistical features are computed on a pixel-wise basis and used in an AdaBoost classifier to extract the blood vessel network inside the image. Finally, the segmented images are postprocessed to remove the misclassified pixels and regions. The proposed method was validated using publicly accessible Digital Retinal Images for Vessel Extraction (DRIVE, Structured Analysis of the Retina (STARE and Child Heart and Health Study in England (CHASE_DB1 datasets commonly used for determining the accuracy of retinal vessel segmentation methods. The accuracy of the proposed segmentation method was comparable to other state of the art methods while being very close to the manual segmentation provided by the second human observer with an average accuracy of 0.972, 0.951 and 0.948 in DRIVE, STARE and CHASE_DB1 datasets, respectively.

Canine and human visual cortex intact and responsive despite early retinal blindness from RPE65 mutation.

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Geoffrey K Aguirre

2007-06-01

Full Text Available RPE65 is an essential molecule in the retinoid-visual cycle, and RPE65 gene mutations cause the congenital human blindness known as Leber congenital amaurosis (LCA. Somatic gene therapy delivered to the retina of blind dogs with an RPE65 mutation dramatically restores retinal physiology and has sparked international interest in human treatment trials for this incurable disease. An unanswered question is how the visual cortex responds after prolonged sensory deprivation from retinal dysfunction. We therefore studied the cortex of RPE65-mutant dogs before and after retinal gene therapy. Then, we inquired whether there is visual pathway integrity and responsivity in adult humans with LCA due to RPE65 mutations (RPE65-LCA.RPE65-mutant dogs were studied with fMRI. Prior to therapy, retinal and subcortical responses to light were markedly diminished, and there were minimal cortical responses within the primary visual areas of the lateral gyrus (activation amplitude mean +/- standard deviation [SD] = 0.07% +/- 0.06% and volume = 1.3 +/- 0.6 cm(3. Following therapy, retinal and subcortical response restoration was accompanied by increased amplitude (0.18% +/- 0.06% and volume (8.2 +/- 0.8 cm(3 of activation within the lateral gyrus (p < 0.005 for both. Cortical recovery occurred rapidly (within a month of treatment and was persistent (as long as 2.5 y after treatment. Recovery was present even when treatment was provided as late as 1-4 y of age. Human RPE65-LCA patients (ages 18-23 y were studied with structural magnetic resonance imaging. Optic nerve diameter (3.2 +/- 0.5 mm was within the normal range (3.2 +/- 0.3 mm, and occipital cortical white matter density as judged by voxel-based morphometry was slightly but significantly altered (1.3 SD below control average, p = 0.005. Functional magnetic resonance imaging in human RPE65-LCA patients revealed cortical responses with a markedly diminished activation volume (8.8 +/- 1.2 cm(3 compared to controls

Rapid and coordinated processing of global motion images by local clusters of retinal ganglion cells.

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Matsumoto, Akihiro; Tachibana, Masao

2017-01-01

Even when the body is stationary, the whole retinal image is always in motion by fixational eye movements and saccades that move the eye between fixation points. Accumulating evidence indicates that the brain is equipped with specific mechanisms for compensating for the global motion induced by these eye movements. However, it is not yet fully understood how the retina processes global motion images during eye movements. Here we show that global motion images evoke novel coordinated firing in retinal ganglion cells (GCs). We simultaneously recorded the firing of GCs in the goldfish isolated retina using a multi-electrode array, and classified each GC based on the temporal profile of its receptive field (RF). A moving target that accompanied the global motion (simulating a saccade following a period of fixational eye movements) modulated the RF properties and evoked synchronized and correlated firing among local clusters of the specific GCs. Our findings provide a novel concept for retinal information processing during eye movements.

Retro-mode imaging and fundus autofluorescence with scanning laser ophthalmoscope of retinal dystrophies

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Maurizio Battaglia

2012-05-01

Full Text Available Abstract Background Retinal dystrophies display a considerably wide range of phenotypic variability, which can make diagnosis and clinical staging difficult. The aim of the study is to analyze the contribution of retro-mode imaging (RMI and fundus autofluorescence (FAF to the characterization of retinal dystrophies. Methods Eighteen consecutive patients affected by retinal dystrophies underwent a complete ophthalmological examination, including best corrected visual acuity with ETDRS charts, blue-light fundus autofluorescence, (BL-FAF, near-infrared fundus autofluorescence (NIR-FAF, and RMI. The primary outcome was the identification of abnormal patterns on RMI. The secondary outcome was the correlation with the findings on BL-FAF and NIR-FAF. Results Overall, the main feature of RMI is represented by a pseudo-3D pattern of all the lesions at the posterior pole. More specifically, any accumulation of material within the retina appears as an area of elevation of different shape and size, displaying irregular and darker borders. No precise correlations between RMI, BL-AF, and NIR-AF imaging was found. Conclusions RMI and FAF appear to be useful tools for characterizing retinal dystrophies. Non-invasive diagnostic tools may yield additional information on the clinical setting and the monitoring of the patients.

Point spread function modeling and image restoration for cone-beam CT

International Nuclear Information System (INIS)

Zhang Hua; Shi Yikai; Huang Kuidong; Xu Zhe

2015-01-01

X-ray cone-beam computed tomography (CT) has such notable features as high efficiency and precision, and is widely used in the fields of medical imaging and industrial non-destructive testing, but the inherent imaging degradation reduces the quality of CT images. Aimed at the problems of projection image degradation and restoration in cone-beam CT, a point spread function (PSF) modeling method is proposed first. The general PSF model of cone-beam CT is established, and based on it, the PSF under arbitrary scanning conditions can be calculated directly for projection image restoration without the additional measurement, which greatly improved the application convenience of cone-beam CT. Secondly, a projection image restoration algorithm based on pre-filtering and pre-segmentation is proposed, which can make the edge contours in projection images and slice images clearer after restoration, and control the noise in the equivalent level to the original images. Finally, the experiments verified the feasibility and effectiveness of the proposed methods. (authors)

Effect of pharmacologically induced retinal degeneration on retinal autofluorescence lifetimes in mice.

Science.gov (United States)

Dysli, Chantal; Dysli, Muriel; Zinkernagel, Martin S; Enzmann, Volker

2016-12-01

Fluorescence lifetime imaging ophthalmoscopy (FLIO) was used to investigate retinal autofluorescence lifetimes in mouse models of pharmacologically induced retinal degeneration over time. Sodium iodate (NaIO 3 , 35 mg/kg intravenously) was used to induce retinal pigment epithelium (RPE) degeneration with subsequent loss of photoreceptors (PR) whereas N-methyl-N-nitrosourea (MNU, 45 mg/kg intraperitoneally) was employed for degeneration of the photoreceptor cell layer alone. All mice were measured at day 3, 7, 14, and 28 after the respective injection of NaIO 3 , MNU or NaCl (control). Fluorescence lifetime imaging was performed using a fluorescence lifetime imaging ophthalmoscope (Heidelberg Engineering, Heidelberg, Germany). Fluorescence was excited at 473 nm and fluorescence lifetimes were measured in a short and a long spectral channel (498-560 nm and 560-720 nm). Corresponding optical coherence tomography (OCT) images were consecutively acquired and histology was performed at the end of the experiments. Segmentation of OCT images and histology verified the cell type-specific degeneration process over time. Retinal autofluorescence lifetimes increased from day 3 to day 28 in mice after NaIO 3 treatment. Finally, at day 28, fluorescence lifetimes were prolonged by 8% in the short and 61% in the long spectral channel compared to control animals (p = 0.21 and p = 0.004, respectively). In mice after MNU treatment, the mean retinal autofluorescence lifetimes were already decreased at day 3 and retinal lifetimes were finally shortened by 27% in the short and 51% in the long spectral channel at day 28 (p = 0.0028). In conclusion, degeneration of the RPE with subsequent photoreceptor degeneration by NaIO 3 lead to longer mean fluorescence lifetimes of the retina compared to control mice, whereas during specific degeneration of the photoreceptor layer induced by MNU shorter lifetimes were measured. Therefore, short retinal fluorescence lifetimes may originate

Large-scale imaging of retinal output activity

CERN Document Server

Litke, A M; Dabrowski, W; Grillo, A A; Grybos, P; Kachiguine, S; Rahman, M; Taylor, G

2003-01-01

A system is being developed to study how the retina processes, encodes and communicates information about the visual world to the brain. It will image the activity of retinal output neurons over a region of live retina approaching that used for significant neural computation in the visual cortex. A prototype system consisting of 61 microelectrodes, covering an area of 0.17 mm**2, is described, including some first results with monkey retina. The plans and status for a system with 512 microelectrodes, covering an area of 1.7 mm**2, are also given.

Optical imaging of mitochondrial redox state in rodent model of retinitis pigmentosa

Science.gov (United States)

Maleki, Sepideh; Gopalakrishnan, Sandeep; Ghanian, Zahra; Sepehr, Reyhaneh; Schmitt, Heather; Eells, Janis; Ranji, Mahsa

2013-01-01

Oxidative stress (OS) and mitochondrial dysfunction contribute to photoreceptor cell loss in retinal degenerative disorders. The metabolic state of the retina in a rodent model of retinitis pigmentosa (RP) was investigated using a cryo-fluorescence imaging technique. The mitochondrial metabolic coenzymes nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) are autofluorescent and can be monitored without exogenous labels using optical techniques. The cryo-fluorescence redox imaging technique provides a quantitative assessment of the metabolism. More specifically, the ratio of the fluorescence intensity of these fluorophores (NADH/FAD), the NADH redox ratio (RR), is a marker of the metabolic state of the tissue. The NADH RR and retinal function were examined in an established rodent model of RP, the P23H rat compared to that of nondystrophic Sprague-Dawley (SD) rats. The NADH RR mean values were 1.11±0.03 in the SD normal and 0.841±0.01 in the P23H retina, indicating increased OS in the P23H retina. Electroretinographic data revealed a significant reduction in photoreceptor function in P23H animals compared to SD nozrmal rats. Thus, cryo-fluorescence redox imaging was used as a quantitative marker of OS in eyes from transgenic rats and demonstrated that alterations in the oxidative state of eyes occur during the early stages of RP.

A Stochastic Approach for Blurred Image Restoration and Optical Flow Computation on Field Image Sequence

Institute of Scientific and Technical Information of China (English)

高文; 陈熙霖

1997-01-01

The blur in target images caused by camera vibration due to robot motion or hand shaking and by object(s) moving in the background scene is different to deal with in the computer vision system.In this paper,the authors study the relation model between motion and blur in the case of object motion existing in video image sequence,and work on a practical computation algorithm for both motion analysis and blut image restoration.Combining the general optical flow and stochastic process,the paper presents and approach by which the motion velocity can be calculated from blurred images.On the other hand,the blurred image can also be restored using the obtained motion information.For solving a problem with small motion limitation on the general optical flow computation,a multiresolution optical flow algoritm based on MAP estimation is proposed. For restoring the blurred image ,an iteration algorithm and the obtained motion velocity are used.The experiment shows that the proposed approach for both motion velocity computation and blurred image restoration works well.

Automated retinal vessel type classification in color fundus images

Science.gov (United States)

Yu, H.; Barriga, S.; Agurto, C.; Nemeth, S.; Bauman, W.; Soliz, P.

2013-02-01

Automated retinal vessel type classification is an essential first step toward machine-based quantitative measurement of various vessel topological parameters and identifying vessel abnormalities and alternations in cardiovascular disease risk analysis. This paper presents a new and accurate automatic artery and vein classification method developed for arteriolar-to-venular width ratio (AVR) and artery and vein tortuosity measurements in regions of interest (ROI) of 1.5 and 2.5 optic disc diameters from the disc center, respectively. This method includes illumination normalization, automatic optic disc detection and retinal vessel segmentation, feature extraction, and a partial least squares (PLS) classification. Normalized multi-color information, color variation, and multi-scale morphological features are extracted on each vessel segment. We trained the algorithm on a set of 51 color fundus images using manually marked arteries and veins. We tested the proposed method in a previously unseen test data set consisting of 42 images. We obtained an area under the ROC curve (AUC) of 93.7% in the ROI of AVR measurement and 91.5% of AUC in the ROI of tortuosity measurement. The proposed AV classification method has the potential to assist automatic cardiovascular disease early detection and risk analysis.

An automated vessel segmentation of retinal images using multiscale vesselness

International Nuclear Information System (INIS)

Ben Abdallah, M.; Malek, J.; Tourki, R.; Krissian, K.

2011-01-01

The ocular fundus image can provide information on pathological changes caused by local ocular diseases and early signs of certain systemic diseases, such as diabetes and hypertension. Automated analysis and interpretation of fundus images has become a necessary and important diagnostic procedure in ophthalmology. The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. In this paper, we introduce an implementation of the anisotropic diffusion which allows reducing the noise and better preserving small structures like vessels in 2D images. A vessel detection filter, based on a multi-scale vesselness function, is then applied to enhance vascular structures.

A multi-step system for screening and localization of hard exudates in retinal images

Science.gov (United States)

Bopardikar, Ajit S.; Bhola, Vishal; Raghavendra, B. S.; Narayanan, Rangavittal

2012-03-01

The number of people being affected by Diabetes mellitus worldwide is increasing at an alarming rate. Monitoring of the diabetic condition and its effects on the human body are therefore of great importance. Of particular interest is diabetic retinopathy (DR) which is a result of prolonged, unchecked diabetes and affects the visual system. DR is a leading cause of blindness throughout the world. At any point of time 25 - 44% of people with diabetes are afflicted by DR. Automation of the screening and monitoring process for DR is therefore essential for efficient utilization of healthcare resources and optimizing treatment of the affected individuals. Such automation would use retinal images and detect the presence of specific artifacts such as hard exudates, hemorrhages and soft exudates (that may appear in the image) to gauge the severity of DR. In this paper, we focus on the detection of hard exudates. We propose a two step system that consists of a screening step that classifies retinal images as normal or abnormal based on the presence of hard exudates and a detection stage that localizes these artifacts in an abnormal retinal image. The proposed screening step automatically detects the presence of hard exudates with a high sensitivity and positive predictive value (PPV ). The detection/localization step uses a k-means based clustering approach to localize hard exudates in the retinal image. Suitable feature vectors are chosen based on their ability to isolate hard exudates while minimizing false detections. The algorithm was tested on a benchmark dataset (DIARETDB1) and was seen to provide a superior performance compared to existing methods. The two-step process described in this paper can be embedded in a tele-ophthalmology system to aid with speedy detection and diagnosis of the severity of DR.

The Role of Retinal Imaging and Portable Screening Devices in Tele-ophthalmology Applications for Diabetic Retinopathy Management.

Science.gov (United States)

DeBuc, Delia Cabrera

2016-12-01

In the years since its introduction, retinal imaging has transformed our capability to visualize the posterior pole of the eye. Increasing practical advances in mobile technology, regular monitoring, and population screening for diabetic retinopathy management offer the opportunity for further development of cost-effective applications through remote assessment of the diabetic eye using portable retinal cameras, smart-phone-based devices and telemedicine networks. Numerous retinal imaging methods and mobile technologies in tele-ophthalmology applications have been reported for diabetic retinopathy screening and management. They provide several advantages of automation, sensitivity, specificity, portability, and miniaturization for the development of point-of-care diagnostics for eye complications in diabetes. The aim of this paper is to review the role of retinal imaging and mobile technologies in tele-ophthalmology applications for diabetic retinopathy screening and management. At large, although improvements in current technology and telemedicine services are still needed, telemedicine has demonstrated to be a worthy tool to support health caregivers in the effective management and prevention of diabetes and its complications.

Automated analysis of retinal images for detection of referable diabetic retinopathy.

Science.gov (United States)

Abràmoff, Michael D; Folk, James C; Han, Dennis P; Walker, Jonathan D; Williams, David F; Russell, Stephen R; Massin, Pascale; Cochener, Beatrice; Gain, Philippe; Tang, Li; Lamard, Mathieu; Moga, Daniela C; Quellec, Gwénolé; Niemeijer, Meindert

2013-03-01

The diagnostic accuracy of computer detection programs has been reported to be comparable to that of specialists and expert readers, but no computer detection programs have been validated in an independent cohort using an internationally recognized diabetic retinopathy (DR) standard. To determine the sensitivity and specificity of the Iowa Detection Program (IDP) to detect referable diabetic retinopathy (RDR). In primary care DR clinics in France, from January 1, 2005, through December 31, 2010, patients were photographed consecutively, and retinal color images were graded for retinopathy severity according to the International Clinical Diabetic Retinopathy scale and macular edema by 3 masked independent retinal specialists and regraded with adjudication until consensus. The IDP analyzed the same images at a predetermined and fixed set point. We defined RDR as more than mild nonproliferative retinopathy and/or macular edema. A total of 874 people with diabetes at risk for DR. Sensitivity and specificity of the IDP to detect RDR, area under the receiver operating characteristic curve, sensitivity and specificity of the retinal specialists' readings, and mean interobserver difference (κ). The RDR prevalence was 21.7% (95% CI, 19.0%-24.5%). The IDP sensitivity was 96.8% (95% CI, 94.4%-99.3%) and specificity was 59.4% (95% CI, 55.7%-63.0%), corresponding to 6 of 874 false-negative results (none met treatment criteria). The area under the receiver operating characteristic curve was 0.937 (95% CI, 0.916-0.959). Before adjudication and consensus, the sensitivity/specificity of the retinal specialists were 0.80/0.98, 0.71/1.00, and 0.91/0.95, and the mean intergrader κ was 0.822. The IDP has high sensitivity and specificity to detect RDR. Computer analysis of retinal photographs for DR and automated detection of RDR can be implemented safely into the DR screening pipeline, potentially improving access to screening and health care productivity and reducing visual loss

Retinal Vessels Segmentation Techniques and Algorithms: A Survey

Directory of Open Access Journals (Sweden)

Jasem Almotiri

2018-01-01

Full Text Available Retinal vessels identification and localization aim to separate the different retinal vasculature structure tissues, either wide or narrow ones, from the fundus image background and other retinal anatomical structures such as optic disc, macula, and abnormal lesions. Retinal vessels identification studies are attracting more and more attention in recent years due to non-invasive fundus imaging and the crucial information contained in vasculature structure which is helpful for the detection and diagnosis of a variety of retinal pathologies included but not limited to: Diabetic Retinopathy (DR, glaucoma, hypertension, and Age-related Macular Degeneration (AMD. With the development of almost two decades, the innovative approaches applying computer-aided techniques for segmenting retinal vessels are becoming more and more crucial and coming closer to routine clinical applications. The purpose of this paper is to provide a comprehensive overview for retinal vessels segmentation techniques. Firstly, a brief introduction to retinal fundus photography and imaging modalities of retinal images is given. Then, the preprocessing operations and the state of the art methods of retinal vessels identification are introduced. Moreover, the evaluation and validation of the results of retinal vessels segmentation are discussed. Finally, an objective assessment is presented and future developments and trends are addressed for retinal vessels identification techniques.

Cnn Based Retinal Image Upscaling Using Zero Component Analysis

Science.gov (United States)

Nasonov, A.; Chesnakov, K.; Krylov, A.

2017-05-01

The aim of the paper is to obtain high quality of image upscaling for noisy images that are typical in medical image processing. A new training scenario for convolutional neural network based image upscaling method is proposed. Its main idea is a novel dataset preparation method for deep learning. The dataset contains pairs of noisy low-resolution images and corresponding noiseless highresolution images. To achieve better results at edges and textured areas, Zero Component Analysis is applied to these images. The upscaling results are compared with other state-of-the-art methods like DCCI, SI-3 and SRCNN on noisy medical ophthalmological images. Objective evaluation of the results confirms high quality of the proposed method. Visual analysis shows that fine details and structures like blood vessels are preserved, noise level is reduced and no artifacts or non-existing details are added. These properties are essential in retinal diagnosis establishment, so the proposed algorithm is recommended to be used in real medical applications.

Optical Coherence Tomography for Retinal Surgery: Perioperative Analysis to Real-Time Four-Dimensional Image-Guided Surgery.

Science.gov (United States)

Carrasco-Zevallos, Oscar M; Keller, Brenton; Viehland, Christian; Shen, Liangbo; Seider, Michael I; Izatt, Joseph A; Toth, Cynthia A

2016-07-01

Magnification of the surgical field using the operating microscope facilitated profound innovations in retinal surgery in the 1970s, such as pars plana vitrectomy. Although surgical instrumentation and illumination techniques are continually developing, the operating microscope for vitreoretinal procedures has remained essentially unchanged and currently limits the surgeon's depth perception and assessment of subtle microanatomy. Optical coherence tomography (OCT) has revolutionized clinical management of retinal pathology, and its introduction into the operating suite may have a similar impact on surgical visualization and treatment. In this article, we review the evolution of OCT for retinal surgery, from perioperative analysis to live volumetric (four-dimensional, 4D) image-guided surgery. We begin by briefly addressing the benefits and limitations of the operating microscope, the progression of OCT technology, and OCT applications in clinical/perioperative retinal imaging. Next, we review intraoperative OCT (iOCT) applications using handheld probes during surgical pauses, two-dimensional (2D) microscope-integrated OCT (MIOCT) of live surgery, and volumetric MIOCT of live surgery. The iOCT discussion focuses on technological advancements, applications during human retinal surgery, translational difficulties and limitations, and future directions.

Matrix Krylov subspace methods for image restoration

Directory of Open Access Journals (Sweden)

khalide jbilou

2015-09-01

Full Text Available In the present paper, we consider some matrix Krylov subspace methods for solving ill-posed linear matrix equations and in those problems coming from the restoration of blurred and noisy images. Applying the well known Tikhonov regularization procedure leads to a Sylvester matrix equation depending the Tikhonov regularized parameter. We apply the matrix versions of the well known Krylov subspace methods, namely the Least Squared (LSQR and the conjugate gradient (CG methods to get approximate solutions representing the restored images. Some numerical tests are presented to show the effectiveness of the proposed methods.

Improved wavefront correction for coherent image restoration.

Science.gov (United States)

Zelenka, Claudius; Koch, Reinhard

2017-08-07

Coherent imaging has a wide range of applications in, for example, microscopy, astronomy, and radar imaging. Particularly interesting is the field of microscopy, where the optical quality of the lens is the main limiting factor. In this article, novel algorithms for the restoration of blurred images in a system with known optical aberrations are presented. Physically motivated by the scalar diffraction theory, the new algorithms are based on Haugazeau POCS and FISTA, and are faster and more robust than methods presented earlier. With the new approach the level of restoration quality on real images is very high, thereby blurring and ringing caused by defocus can be effectively removed. In classical microscopy, lenses with very low aberration must be used, which puts a practical limit on their size and numerical aperture. A coherent microscope using the novel restoration method overcomes this limitation. In contrast to incoherent microscopy, severe optical aberrations including defocus can be removed, hence the requirements on the quality of the optics are lower. This can be exploited for an essential price reduction of the optical system. It can be also used to achieve higher resolution than in classical microscopy, using lenses with high numerical aperture and high aberration. All this makes the coherent microscopy superior to the traditional incoherent in suited applications.

Adaptive Proximal Point Algorithms for Total Variation Image Restoration

Directory of Open Access Journals (Sweden)

Ying Chen

2015-02-01

Full Text Available Image restoration is a fundamental problem in various areas of imaging sciences. This paper presents a class of adaptive proximal point algorithms (APPA with contraction strategy for total variational image restoration. In each iteration, the proposed methods choose an adaptive proximal parameter matrix which is not necessary symmetric. In fact, there is an inner extrapolation in the prediction step, which is followed by a correction step for contraction. And the inner extrapolation is implemented by an adaptive scheme. By using the framework of contraction method, global convergence result and a convergence rate of O(1/N could be established for the proposed methods. Numerical results are reported to illustrate the efficiency of the APPA methods for solving total variation image restoration problems. Comparisons with the state-of-the-art algorithms demonstrate that the proposed methods are comparable and promising.

A fully organic retinal prosthesis restores vision in a rat model of degenerative blindness

Science.gov (United States)

Maya-Vetencourt, José Fernando; Ghezzi, Diego; Antognazza, Maria Rosa; Colombo, Elisabetta; Mete, Maurizio; Feyen, Paul; Desii, Andrea; Buschiazzo, Ambra; di Paolo, Mattia; di Marco, Stefano; Ticconi, Flavia; Emionite, Laura; Shmal, Dmytro; Marini, Cecilia; Donelli, Ilaria; Freddi, Giuliano; Maccarone, Rita; Bisti, Silvia; Sambuceti, Gianmario; Pertile, Grazia; Lanzani, Guglielmo; Benfenati, Fabio

2017-06-01

The degeneration of photoreceptors in the retina is one of the major causes of adult blindness in humans. Unfortunately, no effective clinical treatments exist for the majority of retinal degenerative disorders. Here we report on the fabrication and functional validation of a fully organic prosthesis for long-term in vivo subretinal implantation in the eye of Royal College of Surgeons rats, a widely recognized model of retinitis pigmentosa. Electrophysiological and behavioural analyses reveal a prosthesis-dependent recovery of light sensitivity and visual acuity that persists up to 6-10 months after surgery. The rescue of the visual function is accompanied by an increase in the basal metabolic activity of the primary visual cortex, as demonstrated by positron emission tomography imaging. Our results highlight the possibility of developing a new generation of fully organic, highly biocompatible and functionally autonomous photovoltaic prostheses for subretinal implants to treat degenerative blindness.

Fruit fly optimization based least square support vector regression for blind image restoration

Science.gov (United States)

Zhang, Jiao; Wang, Rui; Li, Junshan; Yang, Yawei

2014-11-01

The goal of image restoration is to reconstruct the original scene from a degraded observation. It is a critical and challenging task in image processing. Classical restorations require explicit knowledge of the point spread function and a description of the noise as priors. However, it is not practical for many real image processing. The recovery processing needs to be a blind image restoration scenario. Since blind deconvolution is an ill-posed problem, many blind restoration methods need to make additional assumptions to construct restrictions. Due to the differences of PSF and noise energy, blurring images can be quite different. It is difficult to achieve a good balance between proper assumption and high restoration quality in blind deconvolution. Recently, machine learning techniques have been applied to blind image restoration. The least square support vector regression (LSSVR) has been proven to offer strong potential in estimating and forecasting issues. Therefore, this paper proposes a LSSVR-based image restoration method. However, selecting the optimal parameters for support vector machine is essential to the training result. As a novel meta-heuristic algorithm, the fruit fly optimization algorithm (FOA) can be used to handle optimization problems, and has the advantages of fast convergence to the global optimal solution. In the proposed method, the training samples are created from a neighborhood in the degraded image to the central pixel in the original image. The mapping between the degraded image and the original image is learned by training LSSVR. The two parameters of LSSVR are optimized though FOA. The fitness function of FOA is calculated by the restoration error function. With the acquired mapping, the degraded image can be recovered. Experimental results show the proposed method can obtain satisfactory restoration effect. Compared with BP neural network regression, SVR method and Lucy-Richardson algorithm, it speeds up the restoration rate and

Hypertensive retinopathy identification through retinal fundus image using backpropagation neural network

Science.gov (United States)

Syahputra, M. F.; Amalia, C.; Rahmat, R. F.; Abdullah, D.; Napitupulu, D.; Setiawan, M. I.; Albra, W.; Nurdin; Andayani, U.

2018-03-01

Hypertension or high blood pressure can cause damage of blood vessels in the retina of eye called hypertensive retinopathy (HR). In the event Hypertension, it will cause swelling blood vessels and a decrese in retina performance. To detect HR in patients body, it is usually performed through physical examination of opthalmoscope which is still conducted manually by an ophthalmologist. Certainly, in such a manual manner, takes a ong time for a doctor to detetct HR on aa patient based on retina fundus iamge. To overcome ths problem, a method is needed to identify the image of retinal fundus automatically. In this research, backpropagation neural network was used as a method for retinal fundus identification. The steps performed prior to identification were pre-processing (green channel, contrast limited adapative histogram qualization (CLAHE), morphological close, background exclusion, thresholding and connected component analysis), feature extraction using zoning. The results show that the proposed method is able to identify retinal fundus with an accuracy of 95% with maximum epoch of 1500.

Histone Deacetylase Inhibition Restores Retinal Pigment Epithelium Function in Hyperglycemia.

Directory of Open Access Journals (Sweden)

Danielle Desjardins

Full Text Available In diabetic individuals, macular edema is a major cause of vision loss. This condition is refractory to insulin therapy and has been attributed to metabolic memory. The retinal pigment epithelium (RPE is central to maintaining fluid balance in the retina, and this function is compromised by the activation of advanced glycation end-product receptors (RAGE. Here we provide evidence that acute administration of the RAGE agonist, glycated-albumin (gAlb or vascular endothelial growth factor (VEGF, increased histone deacetylase (HDAC activity in RPE cells. The administration of the class I/II HDAC inhibitor, trichostatin-A (TSA, suppressed gAlb-induced reductions in RPE transepithelial resistance (in vitro and fluid transport (in vivo. Systemic TSA also restored normal RPE fluid transport in rats with subchronic hyperglycemia. Both gAlb and VEGF increased HDAC activity and reduced acetyl-α-tubulin levels. Tubastatin-A, a relatively specific antagonist of HDAC6, inhibited gAlb-induced changes in RPE cell resistance. These data are consistent with the idea that RPE dysfunction following exposure to gAlb, VEGF, or hyperglycemia is associated with increased HDAC6 activity and decreased acetyl-α-tubulin. Therefore, we propose inhibiting HDAC6 in the RPE as a potential therapy for preserving normal fluid homeostasis in the hyperglycemic retina.

Image Restoration with New Technology

DEFF Research Database (Denmark)

Bülow-Møller, Anne Marie

The article examines the role played by the corporate website while a company - Arla - attempted to restore an image tarnished by unethical behaviour. The company's strategy focussed on dialogue: it introduced a large number of authentic employees in their natural role as cook, dairy farmer, etc....

Bayesian image restoration, using configurations

OpenAIRE

Thorarinsdottir, Thordis

2006-01-01

In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the re...

A Nash-game approach to joint image restoration and segmentation

OpenAIRE

Kallel , Moez; Aboulaich , Rajae; Habbal , Abderrahmane; Moakher , Maher

2014-01-01

International audience; We propose a game theory approach to simultaneously restore and segment noisy images. We define two players: one is restoration, with the image intensity as strategy, and the other is segmentation with contours as strategy. Cost functions are the classical relevant ones for restoration and segmentation, respectively. The two players play a static game with complete information, and we consider as solution to the game the so-called Nash Equilibrium. For the computation ...

Microscope-Integrated Intraoperative Ultrahigh-Speed Swept-Source Optical Coherence Tomography for Widefield Retinal and Anterior Segment Imaging.

Science.gov (United States)

Lu, Chen D; Waheed, Nadia K; Witkin, Andre; Baumal, Caroline R; Liu, Jonathan J; Potsaid, Benjamin; Joseph, Anthony; Jayaraman, Vijaysekhar; Cable, Alex; Chan, Kinpui; Duker, Jay S; Fujimoto, James G

2018-02-01

To demonstrate the feasibility of retinal and anterior segment intraoperative widefield imaging using an ultrahigh-speed, swept-source optical coherence tomography (SS-OCT) surgical microscope attachment. A prototype post-objective SS-OCT using a 1,050-nm wavelength, 400 kHz A-scan rate, vertical cavity surface-emitting laser (VCSEL) light source was integrated to a commercial ophthalmic surgical microscope after the objective. Each widefield OCT data set was acquired in 3 seconds (1,000 × 1,000 A-scans, 12 × 12 mm 2 for retina and 10 × 10 mm 2 for anterior segment). Intraoperative SS-OCT was performed in 20 eyes of 20 patients. In six of seven membrane peels and five of seven rhegmatogenous retinal detachment repair surgeries, widefield retinal imaging enabled evaluation pre- and postoperatively. In all seven cataract cases, anterior imaging evaluated the integrity of the posterior lens capsule. Ultrahigh-speed SS-OCT enables widefield intraoperative viewing in the posterior and anterior eye. Widefield imaging visualizes ocular structures and pathology without requiring OCT realignment. [Ophthalmic Surg Lasers Imaging Retina. 2018;49:94-102.]. Copyright 2018, SLACK Incorporated.

CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition

Science.gov (United States)

Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe

2013-01-01

Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764

Results of Automated Retinal Image Analysis for Detection of Diabetic Retinopathy from the Nakuru Study, Kenya

DEFF Research Database (Denmark)

Juul Bøgelund Hansen, Morten; Abramoff, M. D.; Folk, J. C.

2015-01-01

Objective Digital retinal imaging is an established method of screening for diabetic retinopathy (DR). It has been established that currently about 1% of the world's blind or visually impaired is due to DR. However, the increasing prevalence of diabetes mellitus and DR is creating an increased...... workload on those with expertise in grading retinal images. Safe and reliable automated analysis of retinal images may support screening services worldwide. This study aimed to compare the Iowa Detection Program (IDP) ability to detect diabetic eye diseases (DED) to human grading carried out at Moorfields...... predictive value of IDP versus the human grader as reference standard. Results Altogether 3,460 participants were included. 113 had DED, giving a prevalence of 3.3%(95% CI, 2.7-3.9%). Sensitivity of the IDP to detect DED as by the human grading was 91.0%(95% CI, 88.0-93.4%). The IDP ability to detect DED...

Retinal biometrics based on Iterative Closest Point algorithm.

Science.gov (United States)

Hatanaka, Yuji; Tajima, Mikiya; Kawasaki, Ryo; Saito, Koko; Ogohara, Kazunori; Muramatsu, Chisako; Sunayama, Wataru; Fujita, Hiroshi

2017-07-01

The pattern of blood vessels in the eye is unique to each person because it rarely changes over time. Therefore, it is well known that retinal blood vessels are useful for biometrics. This paper describes a biometrics method using the Jaccard similarity coefficient (JSC) based on blood vessel regions in retinal image pairs. The retinal image pairs were rough matched by the center of their optic discs. Moreover, the image pairs were aligned using the Iterative Closest Point algorithm based on detailed blood vessel skeletons. For registration, perspective transform was applied to the retinal images. Finally, the pairs were classified as either correct or incorrect using the JSC of the blood vessel region in the image pairs. The proposed method was applied to temporal retinal images, which were obtained in 2009 (695 images) and 2013 (87 images). The 87 images acquired in 2013 were all from persons already examined in 2009. The accuracy of the proposed method reached 100%.

Toward automatic phenotyping of retinal images from genetically determined mono- and dizygotic twins using amplitude modulation-frequency modulation methods

Science.gov (United States)

Soliz, P.; Davis, B.; Murray, V.; Pattichis, M.; Barriga, S.; Russell, S.

2010-03-01

This paper presents an image processing technique for automatically categorize age-related macular degeneration (AMD) phenotypes from retinal images. Ultimately, an automated approach will be much more precise and consistent in phenotyping of retinal diseases, such as AMD. We have applied the automated phenotyping to retina images from a cohort of mono- and dizygotic twins. The application of this technology will allow one to perform more quantitative studies that will lead to a better understanding of the genetic and environmental factors associated with diseases such as AMD. A method for classifying retinal images based on features derived from the application of amplitude-modulation frequency-modulation (AM-FM) methods is presented. Retinal images from identical and fraternal twins who presented with AMD were processed to determine whether AM-FM could be used to differentiate between the two types of twins. Results of the automatic classifier agreed with the findings of other researchers in explaining the variation of the disease between the related twins. AM-FM features classified 72% of the twins correctly. Visual grading found that genetics could explain between 46% and 71% of the variance.

Adaptive optics retinal imaging with automatic detection of the pupil and its boundary in real time using Shack-Hartmann images.

Science.gov (United States)

de Castro, Alberto; Sawides, Lucie; Qi, Xiaofeng; Burns, Stephen A

2017-08-20

Retinal imaging with an adaptive optics (AO) system usually requires that the eye be centered and stable relative to the exit pupil of the system. Aberrations are then typically corrected inside a fixed circular pupil. This approach can be restrictive when imaging some subjects, since the pupil may not be round and maintaining a stable head position can be difficult. In this paper, we present an automatic algorithm that relaxes these constraints. An image quality metric is computed for each spot of the Shack-Hartmann image to detect the pupil and its boundary, and the control algorithm is applied only to regions within the subject's pupil. Images on a model eye as well as for five subjects were obtained to show that a system exit pupil larger than the subject's eye pupil could be used for AO retinal imaging without a reduction in image quality. This algorithm automates the task of selecting pupil size. It also may relax constraints on centering the subject's pupil and on the shape of the pupil.

Morphology and Topography of Retinal Pericytes in the Living Mouse Retina Using In Vivo Adaptive Optics Imaging and Ex Vivo Characterization

Science.gov (United States)

Schallek, Jesse; Geng, Ying; Nguyen, HoanVu; Williams, David R.

2013-01-01

Purpose. To noninvasively image retinal pericytes in the living eye and characterize NG2-positive cell topography and morphology in the adult mouse retina. Methods. Transgenic mice expressing fluorescent pericytes (NG2, DsRed) were imaged using a two-channel, adaptive optics scanning laser ophthalmoscope (AOSLO). One channel imaged vascular perfusion with near infrared light. A second channel simultaneously imaged fluorescent retinal pericytes. Mice were also imaged using wide-field ophthalmoscopy. To confirm in vivo imaging, five eyes were enucleated and imaged in flat mount with conventional fluorescent microscopy. Cell topography was quantified relative to the optic disc. Results. We observed strong DsRed fluorescence from NG2-positive cells. AOSLO revealed fluorescent vascular mural cells enveloping all vessels in the living retina. Cells were stellate on larger venules, and showed banded morphology on arterioles. NG2-positive cells indicative of pericytes were found on the smallest capillaries of the retinal circulation. Wide-field SLO enabled quick assessment of NG2-positive distribution, but provided insufficient resolution for cell counts. Ex vivo microscopy showed relatively even topography of NG2-positive capillary pericytes at eccentricities more than 0.3 mm from the optic disc (515 ± 94 cells/mm2 of retinal area). Conclusions. We provide the first high-resolution images of retinal pericytes in the living animal. Subcellular resolution enabled morphological identification of NG2-positive cells on capillaries showing classic features and topography of retinal pericytes. This report provides foundational basis for future studies that will track and quantify pericyte topography, morphology, and function in the living retina over time, especially in the progression of microvascular disease. PMID:24150762

Bayesian image restoration, using configurations

DEFF Research Database (Denmark)

Thorarinsdottir, Thordis

configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed...

Application of the quantum spin glass theory to image restoration.

Science.gov (United States)

Inoue, J I

2001-04-01

Quantum fluctuation is introduced into the Markov random-field model for image restoration in the context of a Bayesian approach. We investigate the dependence of the quantum fluctuation on the quality of a black and white image restoration by making use of statistical mechanics. We find that the maximum posterior marginal (MPM) estimate based on the quantum fluctuation gives a fine restoration in comparison with the maximum a posteriori estimate or the thermal fluctuation based MPM estimate.

Application of the quantum spin glass theory to image restoration

OpenAIRE

Inoue, Jun-ichi

2000-01-01

Quantum fluctuation is introduced into the Markov random-field model for image restoration in the context of a Bayesian approach. We investigate the dependence of the quantum fluctuation on the quality of a black and white image restoration by making use of statistical mechanics. We find that the maximum posterior marginal (MPM) estimate based on the quantum fluctuation gives a fine restoration in comparison with the maximum a posteriori estimate or the thermal fluctuation based MPM estimate.

Detection of microaneurysms in retinal images using an ensemble classifier

Directory of Open Access Journals (Sweden)

M.M. Habib

2017-01-01

Full Text Available This paper introduces, and reports on the performance of, a novel combination of algorithms for automated microaneurysm (MA detection in retinal images. The presence of MAs in retinal images is a pathognomonic sign of Diabetic Retinopathy (DR which is one of the leading causes of blindness amongst the working age population. An extensive survey of the literature is presented and current techniques in the field are summarised. The proposed technique first detects an initial set of candidates using a Gaussian Matched Filter and then classifies this set to reduce the number of false positives. A Tree Ensemble classifier is used with a set of 70 features (the most commons features in the literature. A new set of 32 MA groundtruth images (with a total of 256 labelled MAs based on images from the MESSIDOR dataset is introduced as a public dataset for benchmarking MA detection algorithms. We evaluate our algorithm on this dataset as well as another public dataset (DIARETDB1 v2.1 and compare it against the best available alternative. Results show that the proposed classifier is superior in terms of eliminating false positive MA detection from the initial set of candidates. The proposed method achieves an ROC score of 0.415 compared to 0.2636 achieved by the best available technique. Furthermore, results show that the classifier model maintains consistent performance across datasets, illustrating the generalisability of the classifier and that overfitting does not occur.

Bayesian image restoration, using configurations

DEFF Research Database (Denmark)

Thorarinsdottir, Thordis Linda

2006-01-01

configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for the salt and pepper noise. The inference in the model is discussed...

Rat retinal vasomotion assessed by laser speckle imaging

DEFF Research Database (Denmark)

Neganova, Anastasiia Y; Postnov, Dmitry D; Sosnovtseva, Olga

2017-01-01

Vasomotion is spontaneous or induced rhythmic changes in vascular tone or vessel diameter that lead to rhythmic changes in flow. While the vascular research community debates the physiological and pathophysiological consequence of vasomotion, there is a great need for experimental techniques...... that can address the role and dynamical properties of vasomotion in vivo. We apply laser speckle imaging to study spontaneous and drug induced vasomotion in retinal network of anesthetized rats. The results reveal a wide variety of dynamical patterns. Wavelet-based analysis shows that (i) spontaneous...

Blood Vessel Extraction in Color Retinal Fundus Images with Enhancement Filtering and Unsupervised Classification

Directory of Open Access Journals (Sweden)

Zafer Yavuz

2017-01-01

Full Text Available Retinal blood vessels have a significant role in the diagnosis and treatment of various retinal diseases such as diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. For this reason, retinal vasculature extraction is important in order to help specialists for the diagnosis and treatment of systematic diseases. In this paper, a novel approach is developed to extract retinal blood vessel network. Our method comprises four stages: (1 preprocessing stage in order to prepare dataset for segmentation; (2 an enhancement procedure including Gabor, Frangi, and Gauss filters obtained separately before a top-hat transform; (3 a hard and soft clustering stage which includes K-means and Fuzzy C-means (FCM in order to get binary vessel map; and (4 a postprocessing step which removes falsely segmented isolated regions. The method is tested on color retinal images obtained from STARE and DRIVE databases which are available online. As a result, Gabor filter followed by K-means clustering method achieves 95.94% and 95.71% of accuracy for STARE and DRIVE databases, respectively, which are acceptable for diagnosis systems.

Results of Automated Retinal Image Analysis for Detection of Diabetic Retinopathy from the Nakuru Study, Kenya.

Science.gov (United States)

Hansen, Morten B; Abràmoff, Michael D; Folk, James C; Mathenge, Wanjiku; Bastawrous, Andrew; Peto, Tunde

2015-01-01

Digital retinal imaging is an established method of screening for diabetic retinopathy (DR). It has been established that currently about 1% of the world's blind or visually impaired is due to DR. However, the increasing prevalence of diabetes mellitus and DR is creating an increased workload on those with expertise in grading retinal images. Safe and reliable automated analysis of retinal images may support screening services worldwide. This study aimed to compare the Iowa Detection Program (IDP) ability to detect diabetic eye diseases (DED) to human grading carried out at Moorfields Reading Centre on the population of Nakuru Study from Kenya. Retinal images were taken from participants of the Nakuru Eye Disease Study in Kenya in 2007/08 (n = 4,381 participants [NW6 Topcon Digital Retinal Camera]). First, human grading was performed for the presence or absence of DR, and for those with DR this was sub-divided in to referable or non-referable DR. The automated IDP software was deployed to identify those with DR and also to categorize the severity of DR. The primary outcomes were sensitivity, specificity, and positive and negative predictive value of IDP versus the human grader as reference standard. Altogether 3,460 participants were included. 113 had DED, giving a prevalence of 3.3% (95% CI, 2.7-3.9%). Sensitivity of the IDP to detect DED as by the human grading was 91.0% (95% CI, 88.0-93.4%). The IDP ability to detect DED gave an AUC of 0.878 (95% CI 0.850-0.905). It showed a negative predictive value of 98%. The IDP missed no vision threatening retinopathy in any patients and none of the false negative cases met criteria for treatment. In this epidemiological sample, the IDP's grading was comparable to that of human graders'. It therefore might be feasible to consider inclusion into usual epidemiological grading.

Non-invasive retinal imaging in mice with fluorescent Scanning Laser Ophthalmoscopy and Fourier Domain Optical Coherence Tomography

OpenAIRE

Hossein-Javaheri, Nima

2010-01-01

Visualization of the internal structures of the retina is critical for clinical diagnosis and monitoring of pathology as well as for medical research investigating the root causes of retinal degeneration. The aim of this thesis is to develop multi-modal non-invasive imaging technology for studying retinal degeneration and gene therapy in mice. We have constructed a FD-OCT prototype and combined it with a Scanning Laser Ophthalmoscope (SLO) to permit real time alignment of the retinal field of...

Regenerating reptile retinas: a comparative approach to restoring retinal ganglion cell function.

Science.gov (United States)

Williams, D L

2017-02-01

Transection or damage to the mammalian optic nerve generally results in loss of retinal ganglion cells by apoptosis. This cell death is seen less in fish or amphibians where retinal ganglion cell survival and axon regeneration leads to recovery of sight. Reptiles lie somewhere in the middle of this spectrum of nerve regeneration, and different species have been reported to have a significant variation in their retinal ganglion cell regenerative capacity. The ornate dragon lizard Ctenophoris ornatus exhibits a profound capacity for regeneration, whereas the Tenerife wall lizard Gallotia galloti has a more variable response to optic nerve damage. Some individuals regain visual activity such as the pupillomotor responses, whereas in others axons fail to regenerate sufficiently. Even in Ctenophoris, although the retinal ganglion cell axons regenerate adequately enough to synapse in the tectum, they do not make long-term topographic connections allowing recovery of complex visually motivated behaviour. The question then centres on where these intraspecies differences originate. Is it variation in the innate ability of retinal ganglion cells from different species to regenerate with functional validity? Or is it variances between different species in the substrate within which the nerves regenerate, the extracellular environment of the damaged nerve or the supporting cells surrounding the regenerating axons? Investigations of retinal ganglion cell regeneration between different species of lower vertebrates in vivo may shed light on these questions. Or perhaps more interesting are in vitro studies comparing axon regeneration of retinal ganglion cells from various species placed on differing substrates.

Probabilistic retinal vessel segmentation

Science.gov (United States)

Wu, Chang-Hua; Agam, Gady

2007-03-01

Optic fundus assessment is widely used for diagnosing vascular and non-vascular pathology. Inspection of the retinal vasculature may reveal hypertension, diabetes, arteriosclerosis, cardiovascular disease and stroke. Due to various imaging conditions retinal images may be degraded. Consequently, the enhancement of such images and vessels in them is an important task with direct clinical applications. We propose a novel technique for vessel enhancement in retinal images that is capable of enhancing vessel junctions in addition to linear vessel segments. This is an extension of vessel filters we have previously developed for vessel enhancement in thoracic CT scans. The proposed approach is based on probabilistic models which can discern vessels and junctions. Evaluation shows the proposed filter is better than several known techniques and is comparable to the state of the art when evaluated on a standard dataset. A ridge-based vessel tracking process is applied on the enhanced image to demonstrate the effectiveness of the enhancement filter.

Parallel algorithm of real-time infrared image restoration based on total variation theory

Science.gov (United States)

Zhu, Ran; Li, Miao; Long, Yunli; Zeng, Yaoyuan; An, Wei

2015-10-01

Image restoration is a necessary preprocessing step for infrared remote sensing applications. Traditional methods allow us to remove the noise but penalize too much the gradients corresponding to edges. Image restoration techniques based on variational approaches can solve this over-smoothing problem for the merits of their well-defined mathematical modeling of the restore procedure. The total variation (TV) of infrared image is introduced as a L1 regularization term added to the objective energy functional. It converts the restoration process to an optimization problem of functional involving a fidelity term to the image data plus a regularization term. Infrared image restoration technology with TV-L1 model exploits the remote sensing data obtained sufficiently and preserves information at edges caused by clouds. Numerical implementation algorithm is presented in detail. Analysis indicates that the structure of this algorithm can be easily implemented in parallelization. Therefore a parallel implementation of the TV-L1 filter based on multicore architecture with shared memory is proposed for infrared real-time remote sensing systems. Massive computation of image data is performed in parallel by cooperating threads running simultaneously on multiple cores. Several groups of synthetic infrared image data are used to validate the feasibility and effectiveness of the proposed parallel algorithm. Quantitative analysis of measuring the restored image quality compared to input image is presented. Experiment results show that the TV-L1 filter can restore the varying background image reasonably, and that its performance can achieve the requirement of real-time image processing.

Imaging retinal nerve fiber bundles using optical coherence tomography with adaptive optics.

Science.gov (United States)

Kocaoglu, Omer P; Cense, Barry; Jonnal, Ravi S; Wang, Qiang; Lee, Sangyeol; Gao, Weihua; Miller, Donald T

2011-08-15

Early detection of axonal tissue loss in retinal nerve fiber layer (RNFL) is critical for effective treatment and management of diseases such as glaucoma. This study aims to evaluate the capability of ultrahigh-resolution optical coherence tomography with adaptive optics (UHR-AO-OCT) for imaging the RNFL axonal bundles (RNFBs) with 3×3×3μm(3) resolution in the eye. We used a research-grade UHR-AO-OCT system to acquire 3°×3° volumes in four normal subjects and one subject with an arcuate retinal nerve fiber layer defect (n=5; 29-62years). Cross section (B-scans) and en face (C-scan) slices extracted from the volumes were used to assess visibility and size distribution of individual RNFBs. In one subject, we reimaged the same RNFBs twice over a 7month interval and compared bundle width and thickness between the two imaging sessions. Lastly we compared images of an arcuate RNFL defect acquired with UHR-AO-OCT and commercial OCT (Heidelberg Spectralis). Individual RNFBs were distinguishable in all subjects at 3° retinal eccentricity in both cross-sectional and en face views (width: 30-50μm, thickness: 10-15μm). At 6° retinal eccentricity, RNFBs were distinguishable in three of the five subjects in both views (width: 30-45μm, thickness: 20-40μm). Width and thickness RNFB measurements taken 7months apart were strongly correlated (p<0.0005). Mean difference and standard deviation of the differences between the two measurement sessions were -0.1±4.0μm (width) and 0.3±1.5μm (thickness). UHR-AO-OCT outperformed commercial OCT in terms of clarity of the microscopic retina. To our knowledge, these are the first measurements of RNFB cross section reported in the living human eye. Copyright © 2011 Elsevier Ltd. All rights reserved.

Retinal images in the human eye with implanted intraocular lens

Science.gov (United States)

Zając, Marek; Siedlecki, Damian; Nowak, Jerzy

2007-04-01

A typical proceeding in cataract is based on the removal of opaque crystalline lens and inserting in its place the artificial intraocular lens (IOL). The quality of retinal image after such procedure depends, among others, on the parameters of the IOL, so the design of the implanted lens is of great importance. An appropriate choice of the IOL material, especially in relation to its biocompatibility, is often considered. However the parameter, which is often omitted during the IOL design is its chromatic aberration. In particular lack of its adequacy to the chromatic aberration of a crystalline lens may cause problems. In order to fit better chromatic aberration of the eye with implanted IOL to that of the healthy eye we propose a hybrid - refractive-diffractive IOL. It can be designed in such way that the total longitudinal chromatic aberration of an eye with implanted IOL equals the total longitudinal chromatic aberration of a healthy eye. In this study we compare the retinal image quality calculated numerically on the basis of the well known Liou-Brennan eye model with typical IOL implanted with that obtained if the IOL is done as hybrid (refractive-diffractive) design.

New algorithm for detecting smaller retinal blood vessels in fundus images

Science.gov (United States)

LeAnder, Robert; Bidari, Praveen I.; Mohammed, Tauseef A.; Das, Moumita; Umbaugh, Scott E.

2010-03-01

About 4.1 million Americans suffer from diabetic retinopathy. To help automatically diagnose various stages of the disease, a new blood-vessel-segmentation algorithm based on spatial high-pass filtering was developed to automatically segment blood vessels, including the smaller ones, with low noise. Methods: Image database: Forty, 584 x 565-pixel images were collected from the DRIVE image database. Preprocessing: Green-band extraction was used to obtain better contrast, which facilitated better visualization of retinal blood vessels. A spatial highpass filter of mask-size 11 was applied. A histogram stretch was performed to enhance contrast. A median filter was applied to mitigate noise. At this point, the gray-scale image was converted to a binary image using a binary thresholding operation. Then, a NOT operation was performed by gray-level value inversion between 0 and 255. Postprocessing: The resulting image was AND-ed with its corresponding ring mask to remove the outer-ring (lens-edge) artifact. At this point, the above algorithm steps had extracted most of the major and minor vessels, with some intersections and bifurcations missing. Vessel segments were reintegrated using the Hough transform. Results: After applying the Hough transform, both the average peak SNR and the RMS error improved by 10%. Pratt's Figure of Merit (PFM) was decreased by 6%. Those averages were better than [1] by 10-30%. Conclusions: The new algorithm successfully preserved the details of smaller blood vessels and should prove successful as a segmentation step for automatically identifying diseases that affect retinal blood vessels.

Intraretinal hyperreflective foci on spectral-domain optical coherence tomographic images of patients with retinitis pigmentosa

Science.gov (United States)

Kuroda, Masako; Hirami, Yasuhiko; Hata, Masayuki; Mandai, Michiko; Takahashi, Masayo; Kurimoto, Yasuo

2014-01-01

Background The purpose of this study was to observe the characteristic findings of spectral-domain optical coherence tomography (SD-OCT) images in the retinas of patients with retinitis pigmentosa and to evaluate their distribution patterns in the early and advanced stages of the disease. Methods A total of 184 patients (368 eyes) with retinitis pigmentosa were observed using SD-OCT. We studied the presence or absence of continuous inner/outer segment (IS/OS) lines, presence of thinning of the retinal pigment epithelium-Bruch’s membrane complex, and distribution patterns of hyperreflective foci in the inner and outer nuclear layers (INL and ONL). Results The IS/OS junction had partially disappeared in 275 eyes, which were at the early stage of retinitis pigmentosa (group X), whereas the junction had totally disappeared in 93, which were at the advanced stage of retinitis pigmentosa (group Y). Hyperreflective foci in the INL were observed in a significantly larger proportion of the eyes in group X than in group Y (90% versus 61%, Pretinitis pigmentosa and hyperreflective foci in the ONL were more frequently observed in the advanced stage. Hyperreflective foci may be indicative of changes in the retinal structure at each stage of retinitis pigmentosa. PMID:24591813

Automated detection of kinks from blood vessels for optic cup segmentation in retinal images

Science.gov (United States)

Wong, D. W. K.; Liu, J.; Lim, J. H.; Li, H.; Wong, T. Y.

2009-02-01

The accurate localization of the optic cup in retinal images is important to assess the cup to disc ratio (CDR) for glaucoma screening and management. Glaucoma is physiologically assessed by the increased excavation of the optic cup within the optic nerve head, also known as the optic disc. The CDR is thus an important indicator of risk and severity of glaucoma. In this paper, we propose a method of determining the cup boundary using non-stereographic retinal images by the automatic detection of a morphological feature within the optic disc known as kinks. Kinks are defined as the bendings of small vessels as they traverse from the disc to the cup, providing physiological validation for the cup boundary. To detect kinks, localized patches are first generated from a preliminary cup boundary obtained via level set. Features obtained using edge detection and wavelet transform are combined using a statistical approach rule to identify likely vessel edges. The kinks are then obtained automatically by analyzing the detected vessel edges for angular changes, and these kinks are subsequently used to obtain the cup boundary. A set of retinal images from the Singapore Eye Research Institute was obtained to assess the performance of the method, with each image being clinically graded for the CDR. From experiments, when kinks were used, the error on the CDR was reduced to less than 0.1 CDR units relative to the clinical CDR, which is within the intra-observer variability of 0.2 CDR units.

Analysis of retinal capillaries in patients with type 1 diabetes and nonproliferative diabetic retinopathy using adaptive optics imaging.

Science.gov (United States)

Lombardo, Marco; Parravano, Mariacristina; Serrao, Sebastiano; Ducoli, Pietro; Stirpe, Mario; Lombardo, Giuseppe

2013-09-01

To illustrate a noninvasive method to analyze the retinal capillary lumen caliber in patients with Type 1 diabetes. Adaptive optics imaging of the retinal capillaries were acquired in two parafoveal regions of interest in eyes with nonproliferative diabetic retinopathy and unaffected controls. Measures of the retinal capillary lumen caliber were quantified using an algorithm written in Matlab by an independent observer in a masked manner. Comparison of the adaptive optics images with red-free and color wide fundus retinography images was also assessed. Eight eyes with nonproliferative diabetic retinopathy (eight patients, study group), no macular edema, and preserved visual acuity and eight control eyes (eight healthy volunteers; control group) were analyzed. The repeatability of capillary lumen caliber measurements was 0.22 μm (3.5%) with the 95% confidence interval between 0.12 and 0.31 μm in the study group. It was 0.30 μm (4.1%) with the 95% confidence interval between 0.16 and 0.43 μm in the control group. The average capillary lumen caliber was significantly narrower in eyes with nonproliferative diabetic retinopathy (6.27 ± 1.63 μm) than in the control eyes (7.31 ± 1.59 μm, P = 0.002). The authors demonstrated a noninvasive method to analyze, with micrometric scale of resolution, the lumen of retinal capillaries. The parafoveal capillaries were narrower in patients with Type 1 diabetes and nonproliferative diabetic retinopathy than in healthy subjects, showing the potential capability of adaptive optics imaging to detect pathologic variations of the retinal microvascular structures in vaso-occlusive diseases.

Image quality of the cat eye measured during retinal ganglion cell experiments.

Science.gov (United States)

Bonds, A B; Enroth-Cugell, C; Pinto, L H

1972-01-01

1. The modulation transfer function (MTF) of the dioptrics of fifteen cat eyes was determined. The aerial image, formed by the eye of a standard object (a 0.5-1.0 degrees annulus), was photographed. The transmission of the film negative was measured with a scanning microdensitometer to yield the light distribution within the aerial image. Correcting for the double passage, this experimentally determined light distribution and the known object light distribution were used to obtain the MTF, applying Fourier methods. Each MTF was used to calculate the light distribution within the retinal image of stimuli of various geometry used in experiments on retinal ganglion cells in the same eye.2. When the eye was equipped with an artificial pupil of the same size as that used in the neurophysiological experiments (4.0-4.8 mm diam.) the MTF had fallen to 0.5 at 2.43 c/deg. When the pupil was removed the MTF had fallen to 0.5 at a much lower spatial frequency (1.0 c/deg). This shows that even when one uses an artificial pupil too large to provide optimal image quality there is a vast improvement over using no pupil.3. These image quality measurements were prompted by the need to know the actual stimulus image in experiments on the functional organization of the receptive field, a need exemplified in this paper by a few specific physiological results. The full neurophysiological results appear in the next two papers.

Molecular imaging reveals elevated VEGFR-2 expression in retinal capillaries in diabetes: a novel biomarker for early diagnosis

Science.gov (United States)

Sun, Dawei; Nakao, Shintaro; Xie, Fang; Zandi, Souska; Bagheri, Abouzar; Kanavi, Mozhgan Rezaei; Samiei, Shahram; Soheili, Zahra-Soheila; Frimmel, Sonja; Zhang, Zhongyu; Ablonczy, Zsolt; Ahmadieh, Hamid; Hafezi-Moghadam, Ali

2014-01-01

Diabetic retinopathy (DR) is a microvascular complication of diabetes and a leading cause of vision loss. Biomarkers and methods for early diagnosis of DR are urgently needed. Using a new molecular imaging approach, we show up to 94% higher accumulation of custom designed imaging probes against vascular endothelial growth factor receptor 2 (VEGFR-2) in retinal and choroidal vessels of diabetic animals (PM. R., Samiei, S., Soheili, Z.-S., Frimmel, S., Zhang, Z., Ablonczy, Z., Ahmadieh, H., Hafezi-Moghadam, A. Molecular imaging reveals elevated VEGFR-2 expression in retinal capillaries in diabetes: a novel biomarker for early diagnosis. PMID:24903276

Sequential and parallel image restoration: neural network implementations.

Science.gov (United States)

Figueiredo, M T; Leitao, J N

1994-01-01

Sequential and parallel image restoration algorithms and their implementations on neural networks are proposed. For images degraded by linear blur and contaminated by additive white Gaussian noise, maximum a posteriori (MAP) estimation and regularization theory lead to the same high dimension convex optimization problem. The commonly adopted strategy (in using neural networks for image restoration) is to map the objective function of the optimization problem into the energy of a predefined network, taking advantage of its energy minimization properties. Departing from this approach, we propose neural implementations of iterative minimization algorithms which are first proved to converge. The developed schemes are based on modified Hopfield (1985) networks of graded elements, with both sequential and parallel updating schedules. An algorithm supported on a fully standard Hopfield network (binary elements and zero autoconnections) is also considered. Robustness with respect to finite numerical precision is studied, and examples with real images are presented.

Crowdsourcing and Automated Retinal Image Analysis for Diabetic Retinopathy.

Science.gov (United States)

Mudie, Lucy I; Wang, Xueyang; Friedman, David S; Brady, Christopher J

2017-09-23

As the number of people with diabetic retinopathy (DR) in the USA is expected to increase threefold by 2050, the need to reduce health care costs associated with screening for this treatable disease is ever present. Crowdsourcing and automated retinal image analysis (ARIA) are two areas where new technology has been applied to reduce costs in screening for DR. This paper reviews the current literature surrounding these new technologies. Crowdsourcing has high sensitivity for normal vs abnormal images; however, when multiple categories for severity of DR are added, specificity is reduced. ARIAs have higher sensitivity and specificity, and some commercial ARIA programs are already in use. Deep learning enhanced ARIAs appear to offer even more improvement in ARIA grading accuracy. The utilization of crowdsourcing and ARIAs may be a key to reducing the time and cost burden of processing images from DR screening.

Volumetric fluorescence retinal imaging in vivo over a 30-degree field of view by oblique scanning laser ophthalmoscopy (oSLO).

Science.gov (United States)

Zhang, Lei; Song, Weiye; Shao, Di; Zhang, Sui; Desai, Manishi; Ness, Steven; Roy, Sayon; Yi, Ji

2018-01-01

While fluorescent contrast is widely used in ophthalmology, three-dimensional (3D) fluorescence retinal imaging over a large field of view (FOV) has been challenging. In this paper, we describe a novel oblique scanning laser ophthalmoscopy (oSLO) technique that provides 3D volumetric fluorescence retinal imaging with only one raster scan. The technique utilizes scanned oblique illumination and angled detection to obtain fluorescent cross-sectional images, analogous to optical coherence tomography (OCT) line scans (or B-scans). By breaking the coaxial optical alignment used in conventional retinal imaging modalities, depth resolution is drastically improved. To demonstrate the capability of oSLO, we have performed in vivo volumetric fluorescein angiography (FA) of the rat retina with ~25μm depth resolution and over a 30° FOV. Using depth segmentation, oSLO can obtain high contrast images of the microvasculature down to single capillaries in 3D. The multi-modal nature of oSLO also allows for seamless combination with simultaneous OCT angiography.

Automated microaneurysm detection algorithms applied to diabetic retinopathy retinal images

Directory of Open Access Journals (Sweden)

Akara Sopharak

2013-07-01

Full Text Available Diabetic retinopathy is the commonest cause of blindness in working age people. It is characterised and graded by the development of retinal microaneurysms, haemorrhages and exudates. The damage caused by diabetic retinopathy can be prevented if it is treated in its early stages. Therefore, automated early detection can limit the severity of the disease, improve the follow-up management of diabetic patients and assist ophthalmologists in investigating and treating the disease more efficiently. This review focuses on microaneurysm detection as the earliest clinically localised characteristic of diabetic retinopathy, a frequently observed complication in both Type 1 and Type 2 diabetes. Algorithms used for microaneurysm detection from retinal images are reviewed. A number of features used to extract microaneurysm are summarised. Furthermore, a comparative analysis of reported methods used to automatically detect microaneurysms is presented and discussed. The performance of methods and their complexity are also discussed.

Non-destructive evaluation of teeth restored with different composite resins using synchrotron based micro-imaging.

Science.gov (United States)

Fatima, A; Kulkarni, V K; Banda, N R; Agrawal, A K; Singh, B; Sarkar, P S; Tripathi, S; Shripathi, T; Kashyap, Y; Sinha, A

2016-01-01

Application of high resolution synchrotron micro-imaging in microdefects studies of restored dental samples. The purpose of this study was to identify and compare the defects in restorations done by two different resin systems on teeth samples using synchrotron based micro-imaging techniques namely Phase Contrast Imaging (PCI) and micro-computed tomography (MCT). With this aim acquired image quality was also compared with routinely used RVG (Radiovisiograph). Crowns of human teeth samples were fractured mechanically involving only enamel and dentin, without exposure of pulp chamber and were divided into two groups depending on the restorative composite materials used. Group A samples were restored using a submicron Hybrid composite material and Group B samples were restored using a Nano-Hybrid restorative composite material. Synchrotron based PCI and MCT was performed with the aim of visualization of tooth structure, composite resin and their interface. The quantitative and qualitative comparison of phase contrast and absorption contrast images along with MCT on the restored teeth samples shows comparatively large number of voids in Group A samples. Quality assessment of dental restorations using synchrotron based micro-imaging suggests Nano-Hybrid resin restorations (Group B) are better than Group A.

Retinal nerve fiber layer thickness map determined from optical coherence tomography images

NARCIS (Netherlands)

Mujat, M.; Chan, R. C.; Cense, B.; Park, B.H.; Joo, C.; Akkin, T.; Chen, TC; de Boer, JF

2005-01-01

We introduce a method to determine the retinal nerve fiber layer (RNFL) thickness in OCT images based on anisotropic noise suppression and deformable splines. Spectral-Domain Optical Coherence Tomography (SDOCT) data was acquired at 29 kHz A-line rate with a depth resolution of 2.6 mum and a depth

Restoration of nuclear medicine images using adaptive Wiener filters

International Nuclear Information System (INIS)

Meinel, G.

1989-01-01

An adaptive Wiener filter implementation for restoration of nuclear medicine images is described. These are considerably disturbed both deterministically (definition) and stochastically (Poisson's quantum noise). After introduction of an image model, description of necessary parameter approximations and information on optimum design methods the implementation is described. The filter operates adaptively as concerns the local signal-to-noise ratio and is based on a filter band concept. To verify the restoration effect size numbers are introduced and the filter is tested against these numbers. (author)

In-vivo imaging of blood flow in human retinal vessels using color Doppler optical coherence tomography

Science.gov (United States)

Yazdanfar, Siavash; Rollins, Andrew M.; Izatt, Joseph A.

1999-04-01

Quantification of retinal blood flow may lead to a better understanding of the progression and treatment of several ocular disorders, including diabetic retinopathy, age- related macular degeneration, and glaucoma. Current techniques, such as fluorescein angiography and laser Doppler velocimetry are limited, failing to provide sufficient information to the clinician. Color Doppler optical coherence tomography (CDOCT) is a novel technique using coherent heterodyne detection for simultaneous cross- sectional imaging of tissue microstructure and blood flow. This technique is capable of high spatial and velocity resolution imaging in highly scattering media. We implemented CDOCT for retinal blood flow mapping in human subjects. No dilation of the pupil was necessary. CDOCT is demonstrated for determining bidirectional flow in sub- 100micrometers diameter vessels in the retina. Additionally, we calculated Doppler broadening using the variance of depth- resolved spectra to identify regions with large velocity gradients within the Xenopus heart. This technique may be useful in quantifying local tissue perfusion in highly vascular retinal tissue.

Advanced multiphoton methods for in vitro and in vivo functional imaging of mouse retinal neurons (Conference Presentation)

Science.gov (United States)

Cohen, Noam; Schejter, Adi; Farah, Nairouz; Shoham, Shy

2016-03-01

Studying the responses of retinal ganglion cell (RGC) populations has major significance in vision research. Multiphoton imaging of optogenetic probes has recently become the leading approach for visualizing neural populations and has specific advantages for imaging retinal activity during visual stimulation, because it leads to reduced direct photoreceptor excitation. However, multiphoton retinal activity imaging is not straightforward: point-by-point scanning leads to repeated neural excitation while optical access through the rodent eye in vivo has proven highly challenging. Here, we present two enabling optical designs for multiphoton imaging of responses to visual stimuli in mouse retinas expressing calcium indicators. First, we present an imaging solution based on Scanning Line Temporal Focusing (SLITE) for rapidly imaging neuronal activity in vitro. In this design, we scan a temporally focused line rather than a point, increasing the scan speed and reducing the impact of repeated excitation, while maintaining high optical sectioning. Second, we present the first in vivo demonstration of two-photon imaging of RGC activity in the mouse retina. To obtain these cellular resolution recordings we integrated an illumination path into a correction-free imaging system designed using an optical model of the mouse eye. This system can image at multiple depths using an electronically tunable lens integrated into its optical path. The new optical designs presented here overcome a number of outstanding obstacles, allowing the study of rapid calcium- and potentially even voltage-indicator signals both in vitro and in vivo, thereby bringing us a step closer toward distributed monitoring of action potentials.

Image restoration for civil engineering structure monitoring using imaging system embedded on UAV

Science.gov (United States)

Vozel, Benoit; Dumoulin, Jean; Chehdi, Kacem

2013-04-01

Nowadays, civil engineering structures are periodically surveyed by qualified technicians (i.e. alpinist) operating visual inspection using heavy mechanical pods. This method is far to be safe, not only for civil engineering structures monitoring staff, but also for users. Due to the unceasing traffic increase, making diversions or closing lanes on bridge becomes more and more difficult. New inspection methods have to be found. One of the most promising technique is to develop inspection method using images acquired by a dedicated monitoring system operating around the civil engineering structures, without disturbing the traffic. In that context, the use of images acquired with an UAV, which fly around the structures is of particular interest. The UAV can be equipped with different vision system (digital camera, infrared sensor, video, etc.). Nonetheless, detection of small distresses on images (like cracks of 1 mm or less) depends on image quality, which is sensitive to internal parameters of the UAV (vibration modes, video exposure times, etc.) and to external parameters (turbulence, bad illumination of the scene, etc.). Though progresses were made at UAV level and at sensor level (i.e. optics), image deterioration is still an open problem. These deteriorations are mainly represented by motion blur that can be coupled with out-of-focus blur and observation noise on acquired images. In practice, deteriorations are unknown if no a priori information is available or dedicated additional instrumentation is set-up at UAV level. Image restoration processing is therefore required. This is a difficult problem [1-3] which has been intensively studied over last decades [4-12]. Image restoration can be addressed by following a blind approach or a myopic one. In both cases, it includes two processing steps that can be implemented in sequential or alternate mode. The first step carries out the identification of the blur impulse response and the second one makes use of this

Block iterative restoration of astronomical images with the massively parallel processor

International Nuclear Information System (INIS)

Heap, S.R.; Lindler, D.J.

1987-01-01

A method is described for algebraic image restoration capable of treating astronomical images. For a typical 500 x 500 image, direct algebraic restoration would require the solution of a 250,000 x 250,000 linear system. The block iterative approach is used to reduce the problem to solving 4900 121 x 121 linear systems. The algorithm was implemented on the Goddard Massively Parallel Processor, which can solve a 121 x 121 system in approximately 0.06 seconds. Examples are shown of the results for various astronomical images

LONGITUDINAL STRUCTURAL CHANGES IN LATE-ONSET RETINAL DEGENERATION.

Science.gov (United States)

Cukras, Catherine; Flamendorf, Jason; Wong, Wai T; Ayyagari, Radha; Cunningham, Denise; Sieving, Paul A

2016-12-01

To characterize longitudinal structural changes in early stages of late-onset retinal degeneration to investigate pathogenic mechanisms. Two affected siblings, both with a S163R missense mutation in the causative gene C1QTNF5, were followed for 8+ years. Color fundus photos, fundus autofluorescence images, near-infrared reflectance fundus images, and spectral domain optical coherence tomography scans were acquired during follow-up. Both patients, aged 45 and 50 years, had good visual acuities (>20/20) in the context of prolonged dark adaptation. Baseline color fundus photography demonstrated yellow-white, punctate lesions in the temporal macula that correlated with a reticular pattern on fundus autofluorescence and near-infrared reflectance imaging. Baseline spectral domain optical coherence tomography imaging revealed subretinal deposits that resemble reticular pseudodrusen described in age-related macular degeneration. During follow-up, these affected areas developed confluent thickening of the retinal pigment epithelial layer and disruption of the ellipsoid zone of photoreceptors before progressing to overt retinal pigment epithelium and outer retinal atrophy. Structural changes in early stages of late-onset retinal degeneration, revealed by multimodal imaging, resemble those of reticular pseudodrusen observed in age-related macular degeneration and other retinal diseases. Longitudinal follow-up of these lesions helps elucidate their progression to frank atrophy and may lend insight into the pathogenic mechanisms underlying diverse retinal degenerations.

Imaging retinal degeneration in mice by combining Fourier domain optical coherence tomography and fluorescent scanning laser ophthalmoscopy

Science.gov (United States)

Hossein-Javaheri, Nima; Molday, Laurie L.; Xu, Jing; Molday, Robert S.; Sarunic, Marinko V.

2009-02-01

Visualization of the internal structures of the retina is critical for clinical diagnosis and monitoring of pathology as well as for medical research investigating the root causes of retinal degeneration. Optical Coherence Tomography (OCT) is emerging as the preferred technique for non-contact sub-surface depth-resolved imaging of the retina. The high resolution cross sectional images acquired in vivo by OCT can be compared to histology to visually delineate the retinal layers. The recent demonstration of the significant sensitivity increase obtained through use of Fourier domain (FD) detection with OCT has been used to facilitate high speed scanning for volumetric reconstruction of the retina in software. The images acquired by OCT are purely structural, relying on refractive index differences in the tissue for contrast, and do not provide information on the molecular content of the sample. We have constructed a FDOCT prototype and combined it with a fluorescent Scanning Laser Ophthalmoscope (fSLO) to permit real time alignment of the field of view on the retina. The alignment of the FDOCT system to the specimen is crucial for the registration of measurements taken throughout longitudinal studies. In addition, fluorescence detection has been integrated with the SLO to enable the en face localization of a molecular contrast signal, which is important for retinal angiography, and also for detection of autofluorescence associated with some forms of retinal degeneration, for example autofluorescence lipofuscin accumulations are associated with Stargardt's Macular Dystrophy. The integrated FD OCT/fSLO system was investigated for imaging the retina of the mice in vivo.

Optical imaging of oxidative stress in retinitis pigmentosa (RP) in rodent model

Science.gov (United States)

Ghanian, Zahra; Maleki, Sepideh; Gopalakrishnan, Sandeep; Sepehr, Reyhaneh; Eells, Janis T.; Ranji, Mahsa

2013-02-01

Oxidative stress (OS), which increases during retinal degenerative disorders, contributes to photoreceptor cell loss. The objective of this study was to investigate the changes in the metabolic state of the eye tissue in rodent models of retinitis pigmentosa by using the cryofluorescence imaging technique. The mitochondrial metabolic coenzymes NADH and FADH2 are autofluorescent and can be monitored without exogenous labels using optical techniques. The NADH redox ratio (RR), which is the ratio of the fluorescence intensity of these fluorophores (NADH/FAD), was used as a quantitative diagnostic marker. The NADH RR was examined in an established rodent model of retinitis pigmentosa (RP), the P23H rat, and compared to that of control Sprague-Dawley (SD) rats and P23H NIR treated rats. Our results demonstrated 24% decrease in the mean NADH RR of the eyes from P23H transgenic rats compared to normal rats and 20% increase in the mean NADH RR of the eyes from the P23H NIR treated rats compared to P23H non-treated rats.

Adaptive optics retinal imaging in the living mouse eye

Science.gov (United States)

Geng, Ying; Dubra, Alfredo; Yin, Lu; Merigan, William H.; Sharma, Robin; Libby, Richard T.; Williams, David R.

2012-01-01

Correction of the eye’s monochromatic aberrations using adaptive optics (AO) can improve the resolution of in vivo mouse retinal images [Biss et al., Opt. Lett. 32(6), 659 (2007) and Alt et al., Proc. SPIE 7550, 755019 (2010)], but previous attempts have been limited by poor spot quality in the Shack-Hartmann wavefront sensor (SHWS). Recent advances in mouse eye wavefront sensing using an adjustable focus beacon with an annular beam profile have improved the wavefront sensor spot quality [Geng et al., Biomed. Opt. Express 2(4), 717 (2011)], and we have incorporated them into a fluorescence adaptive optics scanning laser ophthalmoscope (AOSLO). The performance of the instrument was tested on the living mouse eye, and images of multiple retinal structures, including the photoreceptor mosaic, nerve fiber bundles, fine capillaries and fluorescently labeled ganglion cells were obtained. The in vivo transverse and axial resolutions of the fluorescence channel of the AOSLO were estimated from the full width half maximum (FWHM) of the line and point spread functions (LSF and PSF), and were found to be better than 0.79 μm ± 0.03 μm (STD)(45% wider than the diffraction limit) and 10.8 μm ± 0.7 μm (STD)(two times the diffraction limit), respectively. The axial positional accuracy was estimated to be 0.36 μm. This resolution and positional accuracy has allowed us to classify many ganglion cell types, such as bistratified ganglion cells, in vivo. PMID:22574260

Smart image processing system for retinal prosthesis.

Science.gov (United States)

Weiland, James D; Parikh, Neha; Pradeep, Vivek; Medioni, Gerard

2012-01-01

Retinal prostheses for the blind have demonstrated the ability to provide the sensation of light in otherwise blind individuals. However, visual task performance in these patients remains poor relative to someone with normal vision. Computer vision algorithms for navigation and object detection were evaluated for their ability to improve task performance. Blind subjects navigating a mobility course had fewer collisions when using a wearable camera system that guided them on a safe path. Subjects using a retinal prosthesis simulator could locate objects more quickly when an object detection algorithm assisted them. Computer vision algorithms can assist retinal prosthesis patients and low-vision patients in general.

A level-set method for pathology segmentation in fluorescein angiograms and en face retinal images of patients with age-related macular degeneration

Science.gov (United States)

Mohammad, Fatimah; Ansari, Rashid; Shahidi, Mahnaz

2013-03-01

The visibility and continuity of the inner segment outer segment (ISOS) junction layer of the photoreceptors on spectral domain optical coherence tomography images is known to be related to visual acuity in patients with age-related macular degeneration (AMD). Automatic detection and segmentation of lesions and pathologies in retinal images is crucial for the screening, diagnosis, and follow-up of patients with retinal diseases. One of the challenges of using the classical level-set algorithms for segmentation involves the placement of the initial contour. Manually defining the contour or randomly placing it in the image may lead to segmentation of erroneous structures. It is important to be able to automatically define the contour by using information provided by image features. We explored a level-set method which is based on the classical Chan-Vese model and which utilizes image feature information for automatic contour placement for the segmentation of pathologies in fluorescein angiograms and en face retinal images of the ISOS layer. This was accomplished by exploiting a priori knowledge of the shape and intensity distribution allowing the use of projection profiles to detect the presence of pathologies that are characterized by intensity differences with surrounding areas in retinal images. We first tested our method by applying it to fluorescein angiograms. We then applied our method to en face retinal images of patients with AMD. The experimental results included demonstrate that the proposed method provided a quick and improved outcome as compared to the classical Chan-Vese method in which the initial contour is randomly placed, thus indicating the potential to provide a more accurate and detailed view of changes in pathologies due to disease progression and treatment.

Bayesian Image Restoration Using a Large-Scale Total Patch Variation Prior

Directory of Open Access Journals (Sweden)

Yang Chen

2011-01-01

Full Text Available Edge-preserving Bayesian restorations using nonquadratic priors are often inefficient in restoring continuous variations and tend to produce block artifacts around edges in ill-posed inverse image restorations. To overcome this, we have proposed a spatial adaptive (SA prior with improved performance. However, this SA prior restoration suffers from high computational cost and the unguaranteed convergence problem. Concerning these issues, this paper proposes a Large-scale Total Patch Variation (LS-TPV Prior model for Bayesian image restoration. In this model, the prior for each pixel is defined as a singleton conditional probability, which is in a mixture prior form of one patch similarity prior and one weight entropy prior. A joint MAP estimation is thus built to ensure the iteration monotonicity. The intensive calculation of patch distances is greatly alleviated by the parallelization of Compute Unified Device Architecture(CUDA. Experiments with both simulated and real data validate the good performance of the proposed restoration.

Novel method for edge detection of retinal vessels based on the model of the retinal vascular network and mathematical morphology

Science.gov (United States)

Xu, Lei; Zheng, Xiaoxiang; Zhang, Hengyi; Yu, Yajun

1998-09-01

Accurate edge detection of retinal vessels is a prerequisite for quantitative analysis of subtle morphological changes of retinal vessels under different pathological conditions. A novel method for edge detection of retinal vessels is presented in this paper. Methods: (1) Wavelet-based image preprocessing. (2) The signed edge detection algorithm and mathematical morphological operation are applied to get the approximate regions that contain retinal vessels. (3) By convolving the preprocessed image with a LoG operator only on the detected approximate regions of retinal vessels, followed by edges refining, clear edge maps of the retinal vessels are fast obtained. Results: A detailed performance evaluation together with the existing techniques is given to demonstrate the strong features of our method. Conclusions: True edge locations of retinal vessels can be fast detected with continuous structures of retinal vessels, less non- vessel segments left and insensitivity to noise. The method is also suitable for other application fields such as road edge detection.

Autonomous algorithms for image restoration

OpenAIRE

Griniasty , Meir

1994-01-01

We describe a general theoretical framework for algorithms that adaptively tune all their parameters during the restoration of a noisy image. The adaptation procedure is based on a mean field approach which is known as ``Deterministic Annealing'', and is reminiscent of the ``Deterministic Bolzmann Machiné'. The algorithm is less time consuming in comparison with its simulated annealing alternative. We apply the theory to several architectures and compare their performances.

Automatic Detection of Retinal Exudates using a Support Vector Machine

Directory of Open Access Journals (Sweden)

Nualsawat HIRANSAKOLWONG

2013-02-01

Full Text Available Retinal exudates are among the preliminary signs of diabetic retinopathy, a major cause of vision loss in diabetic patients. Correct and efficient screening of exudates is very expensive in professional time and may cause human error. Nowadays, the digital retinal image is frequently used to follow-up and diagnoses eye diseases. Therefore, the retinal image is crucial and essential for experts to detect exudates. Unfortunately, it is a normal situation that retinal images in Thailand are poor quality images. In this paper, we present a series of experiments on feature selection and exudates classification using the support vector machine classifiers. The retinal images are segmented following key preprocessing steps, i.e., color normalization, contrast enhancement, noise removal and color space selection. On data sets of poor quality images, sensitivity, specificity and accuracy is 94.46%, 89.52% and 92.14%, respectively.

Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database.

Science.gov (United States)

Choi, Joon Yul; Yoo, Tae Keun; Seo, Jeong Gi; Kwak, Jiyong; Um, Terry Taewoong; Rim, Tyler Hyungtaek

2017-01-01

Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image has emerged as a new method. We applied deep learning convolutional neural network by using MatConvNet for an automated detection of multiple retinal diseases with fundus photographs involved in STructured Analysis of the REtina (STARE) database. Dataset was built by expanding data on 10 categories, including normal retina and nine retinal diseases. The optimal outcomes were acquired by using a random forest transfer learning based on VGG-19 architecture. The classification results depended greatly on the number of categories. As the number of categories increased, the performance of deep learning models was diminished. When all 10 categories were included, we obtained results with an accuracy of 30.5%, relative classifier information (RCI) of 0.052, and Cohen's kappa of 0.224. Considering three integrated normal, background diabetic retinopathy, and dry age-related macular degeneration, the multi-categorical classifier showed accuracy of 72.8%, 0.283 RCI, and 0.577 kappa. In addition, several ensemble classifiers enhanced the multi-categorical classification performance. The transfer learning incorporated with ensemble classifier of clustering and voting approach presented the best performance with accuracy of 36.7%, 0.053 RCI, and 0.225 kappa in the 10 retinal diseases classification problem. First, due to the small size of datasets, the deep learning techniques in this study were ineffective to be applied in clinics where numerous patients suffering from various types of retinal disorders visit for diagnosis and treatment. Second, we found that the transfer learning incorporated with ensemble classifiers can improve the classification performance in order to detect multi-categorical retinal diseases. Further studies should confirm the effectiveness of algorithms with large datasets obtained from hospitals.

Unsupervised Retinal Vessel Segmentation Using Combined Filters.

Directory of Open Access Journals (Sweden)

Wendeson S Oliveira

Full Text Available Image segmentation of retinal blood vessels is a process that can help to predict and diagnose cardiovascular related diseases, such as hypertension and diabetes, which are known to affect the retinal blood vessels' appearance. This work proposes an unsupervised method for the segmentation of retinal vessels images using a combined matched filter, Frangi's filter and Gabor Wavelet filter to enhance the images. The combination of these three filters in order to improve the segmentation is the main motivation of this work. We investigate two approaches to perform the filter combination: weighted mean and median ranking. Segmentation methods are tested after the vessel enhancement. Enhanced images with median ranking are segmented using a simple threshold criterion. Two segmentation procedures are applied when considering enhanced retinal images using the weighted mean approach. The first method is based on deformable models and the second uses fuzzy C-means for the image segmentation. The procedure is evaluated using two public image databases, Drive and Stare. The experimental results demonstrate that the proposed methods perform well for vessel segmentation in comparison with state-of-the-art methods.

Hugh Grant's Image Restoration Discourse: An Actor Apologizes.

Science.gov (United States)

Benoit, William L.

1997-01-01

Examines the strategies used by actor Hugh Grant (in his appearances on talk shows) to help restore his reputation after he was arrested for lewd behavior with a prostitute. Uses this case as a springboard to contrast entertainment image repair with political and corporate image repair, arguing that important situational differences can be…

Retinal Structure Measurements as Inclusion Criteria for Stem Cell-Based Therapies of Retinal Degenerations.

Science.gov (United States)

Jacobson, Samuel G; Matsui, Rodrigo; Sumaroka, Alexander; Cideciyan, Artur V

2016-04-01

We reviewed and illustrated the most optimal retinal structural measurements to make in stem cell clinical trials. Optical coherence tomography (OCT) and autofluorescence (AF) imaging were used to evaluate patients with severe visual loss from nonsyndromic and syndromic retinitis pigmentosa (RP), ABCA4-Stargardt disease, and nonneovascular age-related macular degeneration (AMD). Outer nuclear layer (ONL), rod outer segment (ROS) layer, inner retina, ganglion cell layer (GCL), and nerve fiber layer (NFL) thicknesses were quantified. All patients had severely reduced visual acuities. Retinitis pigmentosa patients had limited visual fields; maculopathy patients had central scotomas with retained peripheral function. For the forms of RP illustrated, there was detectable albeit severely reduced ONL across the scanned retina, and normal or hyperthick GCL and NFL. Maculopathy patients had no measurable ONL centrally; it became detectable with eccentricity. Some maculopathy patients showed unexpected GCL losses. Autofluorescence imaging illustrated central losses of RPE integrity. A hypothetical scheme to relate patient data with different phases of retinal remodeling in animal models of retinal degeneration was presented. Stem cell science is advancing, but it is not too early to open the discussion of criteria for patient selection and monitoring. Available clinical tools, such as OCT and AF imaging, can provide inclusion/exclusion criteria and robust objective outcomes. Accepting that early trials may not lead to miraculous cures, we should be prepared to know why-scientifically and clinically-so we can improve subsequent trials. We also must determine if retinal remodeling is an impediment to efficacy.

Wavelet domain image restoration with adaptive edge-preserving regularization.

Science.gov (United States)

Belge, M; Kilmer, M E; Miller, E L

2000-01-01

In this paper, we consider a wavelet based edge-preserving regularization scheme for use in linear image restoration problems. Our efforts build on a collection of mathematical results indicating that wavelets are especially useful for representing functions that contain discontinuities (i.e., edges in two dimensions or jumps in one dimension). We interpret the resulting theory in a statistical signal processing framework and obtain a highly flexible framework for adapting the degree of regularization to the local structure of the underlying image. In particular, we are able to adapt quite easily to scale-varying and orientation-varying features in the image while simultaneously retaining the edge preservation properties of the regularizer. We demonstrate a half-quadratic algorithm for obtaining the restorations from observed data.

Fast digital zooming system using directionally adaptive image interpolation and restoration.

Science.gov (United States)

Kang, Wonseok; Jeon, Jaehwan; Yu, Soohwan; Paik, Joonki

2014-01-01

This paper presents a fast digital zooming system for mobile consumer cameras using directionally adaptive image interpolation and restoration methods. The proposed interpolation algorithm performs edge refinement along the initially estimated edge orientation using directionally steerable filters. Either the directionally weighted linear or adaptive cubic-spline interpolation filter is then selectively used according to the refined edge orientation for removing jagged artifacts in the slanted edge region. A novel image restoration algorithm is also presented for removing blurring artifacts caused by the linear or cubic-spline interpolation using the directionally adaptive truncated constrained least squares (TCLS) filter. Both proposed steerable filter-based interpolation and the TCLS-based restoration filters have a finite impulse response (FIR) structure for real time processing in an image signal processing (ISP) chain. Experimental results show that the proposed digital zooming system provides high-quality magnified images with FIR filter-based fast computational structure.

Beyond Retinal Layers: A Deep Voting Model for Automated Geographic Atrophy Segmentation in SD-OCT Images.

Science.gov (United States)

Ji, Zexuan; Chen, Qiang; Niu, Sijie; Leng, Theodore; Rubin, Daniel L

2018-01-01

To automatically and accurately segment geographic atrophy (GA) in spectral-domain optical coherence tomography (SD-OCT) images by constructing a voting system with deep neural networks without the use of retinal layer segmentation. An automatic GA segmentation method for SD-OCT images based on the deep network was constructed. The structure of the deep network was composed of five layers, including one input layer, three hidden layers, and one output layer. During the training phase, the labeled A-scans with 1024 features were directly fed into the network as the input layer to obtain the deep representations. Then a soft-max classifier was trained to determine the label of each individual pixel. Finally, a voting decision strategy was used to refine the segmentation results among 10 trained models. Two image data sets with GA were used to evaluate the model. For the first dataset, our algorithm obtained a mean overlap ratio (OR) 86.94% ± 8.75%, absolute area difference (AAD) 11.49% ± 11.50%, and correlation coefficients (CC) 0.9857; for the second dataset, the mean OR, AAD, and CC of the proposed method were 81.66% ± 10.93%, 8.30% ± 9.09%, and 0.9952, respectively. The proposed algorithm was capable of improving over 5% and 10% segmentation accuracy, respectively, when compared with several state-of-the-art algorithms on two data sets. Without retinal layer segmentation, the proposed algorithm could produce higher segmentation accuracy and was more stable when compared with state-of-the-art methods that relied on retinal layer segmentation results. Our model may provide reliable GA segmentations from SD-OCT images and be useful in the clinical diagnosis of advanced nonexudative AMD. Based on the deep neural networks, this study presents an accurate GA segmentation method for SD-OCT images without using any retinal layer segmentation results, and may contribute to improved understanding of advanced nonexudative AMD.

Two-dimensional restoration of single photon emission computed tomography images using the Kalman filter

International Nuclear Information System (INIS)

Boulfelfel, D.; Rangayyan, R.M.; Kuduvalli, G.R.; Hahn, L.J.; Kloiber, R.

1994-01-01

The discrete filtered backprojection (DFBP) algorithm used for the reconstruction of single photon emission computed tomography (SPECT) images affects image quality because of the operations of filtering and discretization. The discretization of the filtered backprojection process can cause the modulation transfer function (MTF) of the SPECT imaging system to be anisotropic and nonstationary, especially near the edges of the camera's field of view. The use of shift-invariant restoration techniques fails to restore large images because these techniques do not account for such variations in the MTF. This study presents the application of a two-dimensional (2-D) shift-variant Kalman filter for post-reconstruction restoration of SPECT slices. This filter was applied to SPECT images of a hollow cylinder phantom; a resolution phantom; and a large, truncated cone phantom containing two types of cold spots, a sphere, and a triangular prism. The images were acquired on an ADAC GENESYS camera. A comparison was performed between results obtained by the Kalman filter and those obtained by shift-invariant filters. Quantitative analysis of the restored images performed through measurement of root mean squared errors shows a considerable reduction in error of Kalman-filtered images over images restored using shift-invariant methods

Noninvasive near infrared autofluorescence imaging of retinal pigment epithelial cells in the human retina using adaptive optics.

Science.gov (United States)

Liu, Tao; Jung, HaeWon; Liu, Jianfei; Droettboom, Michael; Tam, Johnny

2017-10-01

The retinal pigment epithelial (RPE) cells contain intrinsic fluorophores that can be visualized using infrared autofluorescence (IRAF). Although IRAF is routinely utilized in the clinic for visualizing retinal health and disease, currently, it is not possible to discern cellular details using IRAF due to limits in resolution. We demonstrate that the combination of adaptive optics (AO) with IRAF (AO-IRAF) enables higher-resolution imaging of the IRAF signal, revealing the RPE mosaic in the living human eye. Quantitative analysis of visualized RPE cells in 10 healthy subjects across various eccentricities demonstrates the possibility for in vivo density measurements of RPE cells, which range from 6505 to 5388 cells/mm 2 for the areas measured (peaking at the fovea). We also identified cone photoreceptors in relation to underlying RPE cells, and found that RPE cells support on average up to 18.74 cone photoreceptors in the fovea down to an average of 1.03 cone photoreceptors per RPE cell at an eccentricity of 6 mm. Clinical application of AO-IRAF to a patient with retinitis pigmentosa illustrates the potential for AO-IRAF imaging to become a valuable complementary approach to the current landscape of high resolution imaging modalities.

Blurred image restoration using knife-edge function and optimal window Wiener filtering

Science.gov (United States)

Zhou, Shudao; Yan, Wei

2018-01-01

Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects. PMID:29377950

GPU-based parallel algorithm for blind image restoration using midfrequency-based methods

Science.gov (United States)

Xie, Lang; Luo, Yi-han; Bao, Qi-liang

2013-08-01

GPU-based general-purpose computing is a new branch of modern parallel computing, so the study of parallel algorithms specially designed for GPU hardware architecture is of great significance. In order to solve the problem of high computational complexity and poor real-time performance in blind image restoration, the midfrequency-based algorithm for blind image restoration was analyzed and improved in this paper. Furthermore, a midfrequency-based filtering method is also used to restore the image hardly with any recursion or iteration. Combining the algorithm with data intensiveness, data parallel computing and GPU execution model of single instruction and multiple threads, a new parallel midfrequency-based algorithm for blind image restoration is proposed in this paper, which is suitable for stream computing of GPU. In this algorithm, the GPU is utilized to accelerate the estimation of class-G point spread functions and midfrequency-based filtering. Aiming at better management of the GPU threads, the threads in a grid are scheduled according to the decomposition of the filtering data in frequency domain after the optimization of data access and the communication between the host and the device. The kernel parallelism structure is determined by the decomposition of the filtering data to ensure the transmission rate to get around the memory bandwidth limitation. The results show that, with the new algorithm, the operational speed is significantly increased and the real-time performance of image restoration is effectively improved, especially for high-resolution images.

Determination of retinal surface area.

Science.gov (United States)

Nagra, Manbir; Gilmartin, Bernard; Thai, Ngoc Jade; Logan, Nicola S

2017-09-01

Previous attempts at determining retinal surface area and surface area of the whole eye have been based upon mathematical calculations derived from retinal photographs, schematic eyes and retinal biopsies of donor eyes. 3-dimensional (3-D) ocular magnetic resonance imaging (MRI) allows a more direct measurement, it can be used to image the eye in vivo, and there is no risk of tissue shrinkage. The primary purpose of this study is to compare, using T2-weighted 3D MRI, retinal surface areas for superior-temporal (ST), inferior-temporal (IT), superior-nasal (SN) and inferior-nasal (IN) retinal quadrants. An ancillary aim is to examine whether inter-quadrant variations in area are concordant with reported inter-quadrant patterns of susceptibility to retinal breaks associated with posterior vitreous detachment (PVD). Seventy-three adult participants presenting without retinal pathology (mean age 26.25 ± 6.06 years) were scanned using a Siemens 3-Tesla MRI scanner to provide T2-weighted MR images that demarcate fluid-filled internal structures for the whole eye and provide high-contrast delineation of the vitreous-retina interface. Integrated MRI software generated total internal ocular surface area (TSA). The second nodal point was used to demarcate the origin of the peripheral retina in order to calculate total retinal surface area (RSA) and quadrant retinal surface areas (QRSA) for ST, IT, SN, and IN quadrants. Mean spherical error (MSE) was -2.50 ± 4.03D and mean axial length (AL) 24.51 ± 1.57 mm. Mean TSA and RSA for the RE were 2058 ± 189 and 1363 ± 160 mm 2 , respectively. Repeated measures anova for QRSA data indicated a significant difference within-quadrants (P area/mm increase in AL. Although the differences between QRSAs are relatively small, there was evidence of concordance with reported inter-quadrant patterns of susceptibility to retinal breaks associated with PVD. The data allow AL to be converted to QRSAs, which will assist further

Automatic detection and recognition of multiple macular lesions in retinal optical coherence tomography images with multi-instance multilabel learning

Science.gov (United States)

Fang, Leyuan; Yang, Liumao; Li, Shutao; Rabbani, Hossein; Liu, Zhimin; Peng, Qinghua; Chen, Xiangdong

2017-06-01

Detection and recognition of macular lesions in optical coherence tomography (OCT) are very important for retinal diseases diagnosis and treatment. As one kind of retinal disease (e.g., diabetic retinopathy) may contain multiple lesions (e.g., edema, exudates, and microaneurysms) and eye patients may suffer from multiple retinal diseases, multiple lesions often coexist within one retinal image. Therefore, one single-lesion-based detector may not support the diagnosis of clinical eye diseases. To address this issue, we propose a multi-instance multilabel-based lesions recognition (MIML-LR) method for the simultaneous detection and recognition of multiple lesions. The proposed MIML-LR method consists of the following steps: (1) segment the regions of interest (ROIs) for different lesions, (2) compute descriptive instances (features) for each lesion region, (3) construct multilabel detectors, and (4) recognize each ROI with the detectors. The proposed MIML-LR method was tested on 823 clinically labeled OCT images with normal macular and macular with three common lesions: epiretinal membrane, edema, and drusen. For each input OCT image, our MIML-LR method can automatically identify the number of lesions and assign the class labels, achieving the average accuracy of 88.72% for the cases with multiple lesions, which better assists macular disease diagnosis and treatment.

Retinitis Pigmentosa Sine Pigmento Mimicking a Chiasm Disease.

Science.gov (United States)

Pellegrini, Francesco; Prosdocimo, Giovanni; Romano, Francesco; Interlandi, Emanuela

2017-08-01

A 75-year-old woman presented to her ophthalmologist complaining of visual loss for several years. The ophthalmic examination was remarkable for a bitemporal visual field defect. Magnetic resonance imaging (MRI) scan of the brain was normal without evidence of chiasm compression. Neuro-ophthalmic examination was consistent with a retinal rather than a chiasmal disease. Retinal multimodal imaging helped in the correct diagnosis of retinitis pigmentosa, later confirmed by genetic testing.

Polarimetric imaging of retinal disease by polarization sensitive SLO

Science.gov (United States)

Miura, Masahiro; Elsner, Ann E.; Iwasaki, Takuya; Goto, Hiroshi

2015-03-01

Polarimetry imaging is used to evaluate different features of the macular disease. Polarimetry images were recorded using a commercially- available polarization-sensitive scanning laser opthalmoscope at 780 nm (PS-SLO, GDx-N). From data sets of PS-SLO, we computed average reflectance image, depolarized light images, and ratio-depolarized light images. The average reflectance image is the grand mean of all input polarization states. The depolarized light image is the minimum of crossed channel. The ratio-depolarized light image is a ratio between the average reflectance image and depolarized light image, and was used to compensate for variation of brightness. Each polarimetry image is compared with the autofluorescence image at 800 nm (NIR-AF) and autofluorescence image at 500 nm (SW-AF). We evaluated four eyes with geographic atrophy in age related macular degeneration, one eye with retinal pigment epithelium hyperplasia, and two eyes with chronic central serous chorioretinopathy. Polarization analysis could selectively emphasize different features of the retina. Findings in ratio depolarized light image had similarities and differences with NIR-AF images. Area of hyper-AF in NIR-AF images showed high intensity areas in the ratio depolarized light image, representing melanin accumulation. Areas of hypo-AF in NIR-AF images showed low intensity areas in the ratio depolarized light images, representing melanin loss. Drusen were high-intensity areas in the ratio depolarized light image, but NIR-AF images was insensitive to the presence of drusen. Unlike NIR-AF images, SW-AF images showed completely different features from the ratio depolarized images. Polarization sensitive imaging is an effective tool as a non-invasive assessment of macular disease.

Retinal Thickening and Photoreceptor Loss in HIV Eyes without Retinitis.

Directory of Open Access Journals (Sweden)

Cheryl A Arcinue

Full Text Available To determine the presence of structural changes in HIV retinae (i.e., photoreceptor density and retinal thickness in the macula compared with age-matched HIV-negative controls.Cohort of patients with known HIV under CART (combination Antiretroviral Therapy treatment were examined with a flood-illuminated retinal AO camera to assess the cone photoreceptor mosaic and spectral-domain optical coherence tomography (SD-OCT to assess retinal layers and retinal thickness.Twenty-four eyes of 12 patients (n = 6 HIV-positive and 6 HIV-negative were imaged with the adaptive optics camera. In each of the regions of interest studied (nasal, temporal, superior, inferior, the HIV group had significantly less mean cone photoreceptor density compared with age-matched controls (difference range, 4,308-6,872 cones/mm2. A different subset of forty eyes of 20 patients (n = 10 HIV-positive and 10 HIV-negative was included in the retinal thickness measurements and retinal layer segmentation with the SD-OCT. We observed significant thickening in HIV positive eyes in the total retinal thickness at the foveal center, and in each of the three horizontal B-scans (through the macular center, superior, and inferior to the fovea. We also noted that the inner retina (combined thickness from ILM through RNFL to GCL layer was also significantly thickened in all the different locations scanned compared with HIV-negative controls.Our present study shows that the cone photoreceptor density is significantly reduced in HIV retinae compared with age-matched controls. HIV retinae also have increased macular retinal thickness that may be caused by inner retinal edema secondary to retinovascular disease in HIV. The interaction of photoreceptors with the aging RPE, as well as possible low-grade ocular inflammation causing diffuse inner retinal edema, may be the key to the progressive vision changes in HIV-positive patients without overt retinitis.

MR detection of retinal hemorrhages: correlation with graded ophthalmologic exam

International Nuclear Information System (INIS)

Beavers, Angela J.; Allbery, Sandra M.; Stagner, Anna M.; Hejkal, Thomas W.; Lyden, Elizabeth R.; Haney, Suzanne B.

2015-01-01

Dilated fundoscopic exam is considered the gold standard for detecting retinal hemorrhage, but expertise in obtaining this exam is not always immediately available. MRI can detect retinal hemorrhages, but correlation of the grade or severity of retinal hemorrhage on dilated fundoscopic exam with retinal hemorrhage visibility on MRI has not been described. To determine the value of standard brain protocol MRI in detecting retinal hemorrhage and to determine whether there is any correlation with MR detection of retinal hemorrhage and the dilated fundoscopic exam grade of hemorrhage. We conducted a retrospective chart review of 77 children <2 years old who were seen for head trauma from April 2007 to July 2013 and had both brain MRI and dilated fundoscopic exam or retinal camera images. A staff pediatric radiologist and radiology resident reviewed the MR images. Retinal hemorrhages were graded by a chief ophthalmology resident on a 12-point scale based on the retinal hemorrhage type, size, location and extent as seen on review of retinal camera images and detailed reports by ophthalmologists. Higher scores indicated increased severity of retinal hemorrhages. There was a statistically significant difference in the median grade of retinal hemorrhage examination between children who had retinal hemorrhage detected on MRI and children who did not have retinal hemorrhage detected on MRI (P = 0.02). When examination grade was categorized as low-grade (1-4), moderate-grade (5-8) or high-grade (>8) hemorrhage, there was a statistically significant association between exam grade and diagnosis based on MRI (P = 0.008). For example, only 14% of children with low-grade retinal hemorrhages were identified on MRI compared to 76% of children with high-grade hemorrhages. MR detection of retinal hemorrhage demonstrated a sensitivity of 61%, specificity of 100%, positive predictive value of 100% and negative predictive value of 63%. Retinal hemorrhage was best seen on the gradient

Three-dimensional tomosynthetic image restoration for brachytherapy source localization

International Nuclear Information System (INIS)

Persons, Timothy M.

2001-01-01

Tomosynthetic image reconstruction allows for the production of a virtually infinite number of slices from a finite number of projection views of a subject. If the reconstructed image volume is viewed in toto, and the three-dimensional (3D) impulse response is accurately known, then it is possible to solve the inverse problem (deconvolution) using canonical image restoration methods (such as Wiener filtering or solution by conjugate gradient least squares iteration) by extension to three dimensions in either the spatial or the frequency domains. This dissertation presents modified direct and iterative restoration methods for solving the inverse tomosynthetic imaging problem in 3D. The significant blur artifact that is common to tomosynthetic reconstructions is deconvolved by solving for the entire 3D image at once. The 3D impulse response is computed analytically using a fiducial reference schema as realized in a robust, self-calibrating solution to generalized tomosynthesis. 3D modulation transfer function analysis is used to characterize the tomosynthetic resolution of the 3D reconstructions. The relevant clinical application of these methods is 3D imaging for brachytherapy source localization. Conventional localization schemes for brachytherapy implants using orthogonal or stereoscopic projection radiographs suffer from scaling distortions and poor visibility of implanted seeds, resulting in compromised source tracking (reported errors: 2-4 mm) and dosimetric inaccuracy. 3D image reconstruction (using a well-chosen projection sampling scheme) and restoration of a prostate brachytherapy phantom is used for testing. The approaches presented in this work localize source centroids with submillimeter error in two Cartesian dimensions and just over one millimeter error in the third

Enhanced Visualization of Subtle Outer Retinal Pathology by En Face Optical Coherence Tomography and Correlation with Multi-Modal Imaging.

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Danuta M Sampson

Full Text Available To present en face optical coherence tomography (OCT images generated by graph-search theory algorithm-based custom software and examine correlation with other imaging modalities.En face OCT images derived from high density OCT volumetric scans of 3 healthy subjects and 4 patients using a custom algorithm (graph-search theory and commercial software (Heidelberg Eye Explorer software (Heidelberg Engineering were compared and correlated with near infrared reflectance, fundus autofluorescence, adaptive optics flood-illumination ophthalmoscopy (AO-FIO and microperimetry.Commercial software was unable to generate accurate en face OCT images in eyes with retinal pigment epithelium (RPE pathology due to segmentation error at the level of Bruch's membrane (BM. Accurate segmentation of the basal RPE and BM was achieved using custom software. The en face OCT images from eyes with isolated interdigitation or ellipsoid zone pathology were of similar quality between custom software and Heidelberg Eye Explorer software in the absence of any other significant outer retinal pathology. En face OCT images demonstrated angioid streaks, lesions of acute macular neuroretinopathy, hydroxychloroquine toxicity and Bietti crystalline deposits that correlated with other imaging modalities.Graph-search theory algorithm helps to overcome the limitations of outer retinal segmentation inaccuracies in commercial software. En face OCT images can provide detailed topography of the reflectivity within a specific layer of the retina which correlates with other forms of fundus imaging. Our results highlight the need for standardization of image reflectivity to facilitate quantification of en face OCT images and longitudinal analysis.

Model-based restoration using light vein for range-gated imaging systems.

Science.gov (United States)

Wang, Canjin; Sun, Tao; Wang, Tingfeng; Wang, Rui; Guo, Jin; Tian, Yuzhen

2016-09-10

The images captured by an airborne range-gated imaging system are degraded by many factors, such as light scattering, noise, defocus of the optical system, atmospheric disturbances, platform vibrations, and so on. The characteristics of low illumination, few details, and high noise make the state-of-the-art restoration method fail. In this paper, we present a restoration method especially for range-gated imaging systems. The degradation process is divided into two parts: the static part and the dynamic part. For the static part, we establish the physical model of the imaging system according to the laser transmission theory, and estimate the static point spread function (PSF). For the dynamic part, a so-called light vein feature extraction method is presented to estimate the fuzzy parameter of the atmospheric disturbance and platform movement, which make contributions to the dynamic PSF. Finally, combined with the static and dynamic PSF, an iterative updating framework is used to restore the image. Compared with the state-of-the-art methods, the proposed method can effectively suppress ringing artifacts and achieve better performance in a range-gated imaging system.

Aag-initiated base excision repair drives alkylation-induced retinal degeneration in mice.

Science.gov (United States)

Meira, Lisiane B; Moroski-Erkul, Catherine A; Green, Stephanie L; Calvo, Jennifer A; Bronson, Roderick T; Shah, Dharini; Samson, Leona D

2009-01-20

Vision loss affects >3 million Americans and many more people worldwide. Although predisposing genes have been identified their link to known environmental factors is unclear. In wild-type animals DNA alkylating agents induce photoreceptor apoptosis and severe retinal degeneration. Alkylation-induced retinal degeneration is totally suppressed in the absence of the DNA repair protein alkyladenine DNA glycosylase (Aag) in both differentiating and postmitotic retinas. Moreover, transgenic expression of Aag activity restores the alkylation sensitivity of photoreceptors in Aag null animals. Aag heterozygotes display an intermediate level of retinal degeneration, demonstrating haploinsufficiency and underscoring that Aag expression confers a dominant retinal degeneration phenotype.

Phenotypic diversity in autosomal-dominant cone-rod dystrophy elucidated by adaptive optics retinal imaging.

Science.gov (United States)

Song, Hongxin; Rossi, Ethan A; Stone, Edwin; Latchney, Lisa; Williams, David; Dubra, Alfredo; Chung, Mina

2018-01-01

Several genes causing autosomal-dominant cone-rod dystrophy (AD-CRD) have been identified. However, the mechanisms by which genetic mutations lead to cellular loss in human disease remain poorly understood. Here we combine genotyping with high-resolution adaptive optics retinal imaging to elucidate the retinal phenotype at a cellular level in patients with AD-CRD harbouring a defect in the GUCA1A gene. Nine affected members of a four-generation AD-CRD pedigree and three unaffected first-degree relatives underwent clinical examinations including visual acuity, fundus examination, Goldmann perimetry, spectral domain optical coherence tomography and electroretinography. Genome-wide scan followed by bidirectional sequencing was performed on all affected participants. High-resolution imaging using a custom adaptive optics scanning light ophthalmoscope (AOSLO) was performed for selected participants. Clinical evaluations showed a range of disease severity from normal fundus appearance in teenaged patients to pronounced macular atrophy in older patients. Molecular genetic testing showed a mutation in in GUCA1A segregating with disease. AOSLO imaging revealed that of the two teenage patients with mild disease, one had severe disruption of the photoreceptor mosaic while the other had a normal cone mosaic. AOSLO imaging demonstrated variability in the pattern of cone and rod cell loss between two teenage cousins with early AD-CRD, who had similar clinical features and had the identical disease-causing mutation in GUCA1A . This finding suggests that a mutation in GUCA1A does not lead to the same degree of AD-CRD in all patients. Modifying factors may mitigate or augment disease severity, leading to different retinal cellular phenotypes. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

INTERNAL LIMITING MEMBRANE PEELING-DEPENDENT RETINAL STRUCTURAL CHANGES AFTER VITRECTOMY IN RHEGMATOGENOUS RETINAL DETACHMENT.

Science.gov (United States)

Hisatomi, Toshio; Tachibana, Takashi; Notomi, Shoji; Koyanagi, Yoshito; Murakami, Yusuke; Takeda, Atsunobu; Ikeda, Yasuhiro; Yoshida, Shigeo; Enaida, Hiroshi; Murata, Toshinori; Sakamoto, Taiji; Sonoda, Koh-Hei; Ishibashi, Tatsuro

2018-03-01

To examine retinal changes after vitrectomy with internal limiting membrane (ILM) peeling, we used 3-dimensional optical coherence tomography (3D-OCT) in rhegmatogenous retinal detachment cases. The 68 eyes from 67 patients with rhegmatogenous retinal detachment were studied, including 35 detached macula cases (51%) and 33 attached macula cases. Internal limiting membrane peeling was performed with fine forceps after brilliant blue G staining. The 3D-OCT images were obtained with volume-rendering technologies from cross-sectional OCT images. The 3D-OCT detected 45 eyes (66%) with ILM peeling-dependent retinal changes, including dissociated optic nerve fiber layer appearance, dimple sign, temporal macular thinning, ILM peeling area thinning, or forceps-related retinal thinning. The ILM peeled area was detectable in only 9 eyes with 3D-OCT, whereas it was undetectable in other 59 eyes. The dissociated optic nerve fiber layer appearance was detected in 8 of the total cases (12%), and dimple signs were observed in 14 cases (21%). Forceps-related thinning was also noted in eight cases (24%) of attached macula cases and in four cases (11%) of detached macula cases. No postoperative macular pucker was noted in the observational period. The 3D-OCT clearly revealed spatial and time-dependent retinal changes after ILM peeling. The changes occurred in 2 months and remained thereafter.

High-resolution retinal imaging using adaptive optics and Fourier-domain optical coherence tomography

Science.gov (United States)

Olivier, Scot S.; Werner, John S.; Zawadzki, Robert J.; Laut, Sophie P.; Jones, Steven M.

2010-09-07

This invention permits retinal images to be acquired at high speed and with unprecedented resolution in three dimensions (4.times.4.times.6 .mu.m). The instrument achieves high lateral resolution by using adaptive optics to correct optical aberrations of the human eye in real time. High axial resolution and high speed are made possible by the use of Fourier-domain optical coherence tomography. Using this system, we have demonstrated the ability to image microscopic blood vessels and the cone photoreceptor mosaic.

BAYESIAN IMAGE RESTORATION, USING CONFIGURATIONS

Directory of Open Access Journals (Sweden)

Thordis Linda Thorarinsdottir

2011-05-01

Full Text Available In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed in detail for 3 X 3 and 5 X 5 configurations and examples of the performance of the procedure are given.

Retinal vascular imaging technology to monitor disease severity and complications in type 1 diabetes mellitus: A systematic review.

Science.gov (United States)

Kee, Ae Ra; Wong, Tien Yin; Li, Ling-Jun

2017-02-01

Type 1 diabetes mellitus (T1DM) is a major disease affecting a large number of young patients. In the recent years, retinal vascular imaging has provided an objective assessment of vascular health in patients with T1DM. Our study aimed to review the current literature on retinal vascular parameters in young patients with T1DM in order to understand the following: (i) How retinal vessels are affected in T1DM (ii) How such vascular changes can be predictive of future diabetic microvascular complications METHODS: We performed a systematic review and extracted relevant data from 17 articles. We found significant correlations between retinal vessel changes and diabetes-related risk factors (eg, hypertension, hyperlipidemia, and obesity), diabetes-related features (eg, diabetes duration and glycemic control), and diabetes-related microvascular complications (eg, diabetic retinopathy, nephropathy, and neuropathy). Our findings suggest that retinal microvasculature is associated with both disease severity and complications in young patients with T1DM. © 2016 John Wiley & Sons Ltd.

The mean field theory in EM procedures for blind Markov random field image restoration.

Science.gov (United States)

Zhang, J

1993-01-01

A Markov random field (MRF) model-based EM (expectation-maximization) procedure for simultaneously estimating the degradation model and restoring the image is described. The MRF is a coupled one which provides continuity (inside regions of smooth gray tones) and discontinuity (at region boundaries) constraints for the restoration problem which is, in general, ill posed. The computational difficulty associated with the EM procedure for MRFs is resolved by using the mean field theory from statistical mechanics. An orthonormal blur decomposition is used to reduce the chances of undesirable locally optimal estimates. Experimental results on synthetic and real-world images show that this approach provides good blur estimates and restored images. The restored images are comparable to those obtained by a Wiener filter in mean-square error, but are most visually pleasing.

Study on monitoring ecological restoration in Jiuli mining area by SAR image

Science.gov (United States)

Wei, Na; Chen, Fu; Tang, Qian

2011-10-01

The ecological restoration in mining area is one of the study hot spots in the field of resources and environment at present. The vegetation biomass is used as the ecological restoration evaluation index in mining area in the paper. The synthetic aperture radar image after ecological restoration in mining area is used to classify different kinds of vegetation covers. Integrating the field data and the data of L band, the average total backward scattering coefficient which corresponds to the synthetic aperture radar image is calculated and the relation model between the average total backward scattering coefficient and vegetation biomass is established. At last the vegetation biomass is assessed in Jiuli mining area. The results show that the vegetation biomass characteristics which are assessed by using synthetic aperture radar image data and the field data of vegetation biomass characteristics have better consistency in Jiuli mining area. The effects of ecological restoration can be evaluated by using this relation model effectively and accurately.

Artificial vision: needs, functioning, and testing of a retinal electronic prosthesis.

Science.gov (United States)

Chader, Gerald J; Weiland, James; Humayun, Mark S

2009-01-01

Hundreds of thousands around the world have poor vision or no vision at all due to inherited retinal degenerations (RDs) like retinitis pigmentosa (RP). Similarly, millions suffer from vision loss due to age-related macular degeneration (AMD). In both of these allied diseases, the primary target for pathology is the retinal photoreceptor cells that dysfunction and die. Secondary neurons though are relatively spared. To replace photoreceptor cell function, an electronic prosthetic device can be used such that retinal secondary neurons receive a signal that simulates an external visual image. The composite device has a miniature video camera mounted on the patient's eyeglasses, which captures images and passes them to a microprocessor that converts the data to an electronic signal. This signal, in turn, is transmitted to an array of electrodes placed on the retinal surface, which transmits the patterned signal to the remaining viable secondary neurons. These neurons (ganglion, bipolar cells, etc.) begin processing the signal and pass it down the optic nerve to the brain for final integration into a visual image. Many groups in different countries have different versions of the device, including brain implants and retinal implants, the latter having epiretinal or subretinal placement. The device furthest along in development is an epiretinal implant sponsored by Second Sight Medical Products (SSMP). Their first-generation device had 16 electrodes with human testing in a Phase 1 clinical trial beginning in 2002. The second-generation device has 60+ electrodes and is currently in Phase 2/3 clinical trial. Increased numbers of electrodes are planned for future versions of the device. Testing of the device's efficacy is a challenge since patients admitted into the trial have little or no vision. Thus, methods must be developed that accurately and reproducibly record small improvements in visual function after implantation. Standard tests such as visual acuity, visual

An image-processing strategy to extract important information suitable for a low-size stimulus pattern in a retinal prosthesis.

Science.gov (United States)

Chen, Yili; Fu, Jixiang; Chu, Dawei; Li, Rongmao; Xie, Yaoqin

2017-11-27

A retinal prosthesis is designed to help the blind to obtain some sight. It consists of an external part and an internal part. The external part is made up of a camera, an image processor and an RF transmitter. The internal part is made up of an RF receiver, implant chip and microelectrode. Currently, the number of microelectrodes is in the hundreds, and we do not know the mechanism for using an electrode to stimulate the optic nerve. A simple hypothesis is that the pixels in an image correspond to the electrode. The images captured by the camera should be processed by suitable strategies to correspond to stimulation from the electrode. Thus, it is a question of how to obtain the important information from the image captured in the picture. Here, we use the region of interest (ROI), a useful algorithm for extracting the ROI, to retain the important information, and to remove the redundant information. This paper explains the details of the principles and functions of the ROI. Because we are investigating a real-time system, we need a fast processing ROI as a useful algorithm to extract the ROI. Thus, we simplified the ROI algorithm and used it in an outside image-processing digital signal processing (DSP) system of the retinal prosthesis. The results show that our image-processing strategies are suitable for a real-time retinal prosthesis and can eliminate redundant information and provide useful information for expression in a low-size image.

Optic disc detection and boundary extraction in retinal images.

Science.gov (United States)

Basit, A; Fraz, Muhammad Moazam

2015-04-10

With the development of digital image processing, analysis and modeling techniques, automatic retinal image analysis is emerging as an important screening tool for early detection of ophthalmologic disorders such as diabetic retinopathy and glaucoma. In this paper, a robust method for optic disc detection and extraction of the optic disc boundary is proposed to help in the development of computer-assisted diagnosis and treatment of such ophthalmic disease. The proposed method is based on morphological operations, smoothing filters, and the marker controlled watershed transform. Internal and external markers are used to first modify the gradient magnitude image and then the watershed transformation is applied on this modified gradient magnitude image for boundary extraction. This method has shown significant improvement over existing methods in terms of detection and boundary extraction of the optic disc. The proposed method has optic disc detection success rate of 100%, 100%, 100% and 98.9% for the DRIVE, Shifa, CHASE_DB1, and DIARETDB1 databases, respectively. The optic disc boundary detection achieved an average spatial overlap of 61.88%, 70.96%, 45.61%, and 54.69% for these databases, respectively, which are higher than currents methods.

Neural Network Blind Equalization Algorithm Applied in Medical CT Image Restoration

Directory of Open Access Journals (Sweden)

Yunshan Sun

2013-01-01

Full Text Available A new algorithm for iterative blind image restoration is presented in this paper. The method extends blind equalization found in the signal case to the image. A neural network blind equalization algorithm is derived and used in conjunction with Zigzag coding to restore the original image. As a result, the effect of PSF can be removed by using the proposed algorithm, which contributes to eliminate intersymbol interference (ISI. In order to obtain the estimation of the original image, what is proposed in this method is to optimize constant modulus blind equalization cost function applied to grayscale CT image by using conjugate gradient method. Analysis of convergence performance of the algorithm verifies the feasibility of this method theoretically; meanwhile, simulation results and performance evaluations of recent image quality metrics are provided to assess the effectiveness of the proposed method.

Determination of point spread function for a flat-panel X-ray imager and its application in image restoration

International Nuclear Information System (INIS)

Jeon, Sungchae; Cho, Gyuseong; Huh, Young; Jin, Seungoh; Park, Jongduk

2006-01-01

We investigate the image blur estimation methods, namely modified the Richardson-Lucy (R-L) estimator and the Wiener estimator. Based on the empirical model of the PSF, an image restoration is applied to radiological images. The accuracy of the PSF estimation under the Poisson noise and readout electronic noise is significantly better for the R-L estimator than the Wiener estimator. In the image restoration using the 2-D PSF from the R-L estimator, the result shows a good improvement in the low and middle range of spatial frequency

Noninvasive Imaging of Retinal Morphology and Microvasculature in Obese Mice Using Optical Coherence Tomography and Optical Microangiography

Science.gov (United States)

Zhi, Zhongwei; Chao, Jennifer R.; Wietecha, Tomasz; Hudkins, Kelly L.; Alpers, Charles E.; Wang, Ruikang K.

2014-01-01

Purpose. To evaluate early diabetes-induced changes in retinal thickness and microvasculature in a type 2 diabetic mouse model by using optical coherence tomography (OCT)/optical microangiography (OMAG). Methods. Twenty-two-week-old obese (OB) BTBR mice (n = 10) and wild-type (WT) control mice (n = 10) were imaged. Three-dimensional (3D) data volumes were captured with spectral domain OCT using an ultrahigh-sensitive OMAG scanning protocol for 3D volumetric angiography of the retina and dense A-scan protocol for measurement of the total retinal blood flow (RBF) rate. The thicknesses of the nerve fiber layer (NFL) and that of the NFL to the inner plexiform layer (IPL) were measured and compared between OB and WT mice. The linear capillary densities within intermediate and deep capillary layers were determined by the number of capillaries crossing a 500-μm line. The RBF rate was evaluated using an en face Doppler approach. These quantitative measurements were compared between OB and WT mice. Results. The retinal thickness of the NFL to IPL was significantly reduced in OB mice (P < 0.01) compared to that in WT mice, whereas the NFL thickness between the two was unchanged. 3D depth-resolved OMAG angiography revealed the first in vivo 3D model of mouse retinal microcirculation. Although no obvious differences in capillary vessel densities of the intermediate and deep capillary layers were detected between normal and OB mice, the total RBF rate was significantly lower (P < 0.05) in OB mice than in WT mice. Conclusions. We conclude that OB BTBR mice have significantly reduced NFL–IPL thicknesses and total RBF rates compared with those of WT mice, as imaged by OCT/OMAG. OMAG provides an unprecedented capability for high-resolution depth-resolved imaging of mouse retinal vessels and blood flow that may play a pivotal role in providing a noninvasive method for detecting early microvascular changes in patients with diabetic retinopathy. PMID:24458155

Optimization of hybrid imaging systems based on maximization of kurtosis of the restored point spread function

DEFF Research Database (Denmark)

Demenikov, Mads

2011-01-01

to optimization results based on full-reference image measures of restored images. In comparison with full-reference measures, the kurtosis measure is fast to compute and requires no images, noise distributions, or alignment of restored images, but only the signal-to-noise-ratio. © 2011 Optical Society of America.......I propose a novel, but yet simple, no-reference, objective image quality measure based on the kurtosis of the restored point spread function. Using this measure, I optimize several phase masks for extended-depth-of-field in hybrid imaging systems and obtain results that are identical...

Dynamic simulation of the effect of soft toric contact lenses movement on retinal image quality.

Science.gov (United States)

Niu, Yafei; Sarver, Edwin J; Stevenson, Scott B; Marsack, Jason D; Parker, Katrina E; Applegate, Raymond A

2008-04-01

To report the development of a tool designed to dynamically simulate the effect of soft toric contact lens movement on retinal image quality, initial findings on three eyes, and the next steps to be taken to improve the utility of the tool. Three eyes of two subjects wearing soft toric contact lenses were cyclopleged with 1% cyclopentolate and 2.5% phenylephrine. Four hundred wavefront aberration measurements over a 5-mm pupil were recorded during soft contact lens wear at 30 Hz using a complete ophthalmic analysis system aberrometer. Each wavefront error measurement was input into Visual Optics Laboratory (version 7.15, Sarver and Associates, Inc.) to generate a retinal simulation of a high contrast log MAR visual acuity chart. The individual simulations were combined into a single dynamic movie using a custom MatLab PsychToolbox program. Visual acuity was measured for each eye reading the movie with best cycloplegic spectacle correction through a 3-mm artificial pupil to minimize the influence of the eyes' uncorrected aberrations. Comparison of the simulated acuity was made to values recorded while the subject read unaberrated charts with contact lenses through a 5-mm artificial pupil. For one study eye, average acuity was the same as the natural contact lens viewing condition. For the other two study eyes visual acuity of the best simulation was more than one line worse than natural viewing conditions. Dynamic simulation of retinal image quality, although not yet perfect, is a promising technique for visually illustrating the optical effects on image quality because of the movements of alignment-sensitive corrections.

Gene Correction Reverses Ciliopathy and Photoreceptor Loss in iPSC-Derived Retinal Organoids from Retinitis Pigmentosa Patients

Directory of Open Access Journals (Sweden)

Wen-Li Deng

2018-04-01

Full Text Available Summary: Retinitis pigmentosa (RP is an irreversible, inherited retinopathy in which early-onset nyctalopia is observed. Despite the genetic heterogeneity of RP, RPGR mutations are the most common causes of this disease. Here, we generated induced pluripotent stem cells (iPSCs from three RP patients with different frameshift mutations in the RPGR gene, which were then differentiated into retinal pigment epithelium (RPE cells and well-structured retinal organoids possessing electrophysiological properties. We observed significant defects in photoreceptor in terms of morphology, localization, transcriptional profiling, and electrophysiological activity. Furthermore, shorted cilium was found in patient iPSCs, RPE cells, and three-dimensional retinal organoids. CRISPR-Cas9-mediated correction of RPGR mutation rescued photoreceptor structure and electrophysiological property, reversed the observed ciliopathy, and restored gene expression to a level in accordance with that in the control using transcriptome-based analysis. This study recapitulated the pathogenesis of RPGR using patient-specific organoids and achieved targeted gene therapy of RPGR mutations in a dish as proof-of-concept evidence. : Jin and colleagues demonstrate that patient-specific iPSC-derived 3D retinae can recapitulate disease progress of retinitis pigmentosa through presenting defects in photoreceptor morphology, gene profile, and electrophysiology, as well as the defective ciliogenesis in iPSCs, iPSC-RPE, and 3D retinae. CRISPR/Cas9-mediated gene correction can rescue not only photoreceptor structure and electrophysiological property but also observed ciliopathy. Keywords: RPGR, photoreceptor, electrophysiology, retinitis pigmentosa, patient-derived iPSCs, retinal organoid, RPE cells, cilium, ciliopathy, disease modeling

l0TV: A Sparse Optimization Method for Impulse Noise Image Restoration

KAUST Repository

Yuan, Ganzhao; Ghanem, Bernard

2017-01-01

Total Variation (TV) is an effective and popular prior model in the field of regularization-based image processing. This paper focuses on total variation for removing impulse noise in image restoration. This type of noise frequently arises in data acquisition and transmission due to many reasons, e.g. a faulty sensor or analog-to-digital converter errors. Removing this noise is an important task in image restoration. State-of-the-art methods such as Adaptive Outlier Pursuit(AOP), which is based on TV with l02-norm data fidelity, only give sub-optimal performance. In this paper, we propose a new sparse optimization method, called l0TV-PADMM, which solves the TV-based restoration problem with l0-norm data fidelity. To effectively deal with the resulting non-convex non-smooth optimization problem, we first reformulate it as an equivalent biconvex Mathematical Program with Equilibrium Constraints (MPEC), and then solve it using a proximal Alternating Direction Method of Multipliers (PADMM). Our l0TV-PADMM method finds a desirable solution to the original l0-norm optimization problem and is proven to be convergent under mild conditions. We apply l0TV-PADMM to the problems of image denoising and deblurring in the presence of impulse noise. Our extensive experiments demonstrate that l0TV-PADMM outperforms state-of-the-art image restoration methods.

l0TV: A Sparse Optimization Method for Impulse Noise Image Restoration

KAUST Repository

Yuan, Ganzhao

2017-12-18

Total Variation (TV) is an effective and popular prior model in the field of regularization-based image processing. This paper focuses on total variation for removing impulse noise in image restoration. This type of noise frequently arises in data acquisition and transmission due to many reasons, e.g. a faulty sensor or analog-to-digital converter errors. Removing this noise is an important task in image restoration. State-of-the-art methods such as Adaptive Outlier Pursuit(AOP), which is based on TV with l02-norm data fidelity, only give sub-optimal performance. In this paper, we propose a new sparse optimization method, called l0TV-PADMM, which solves the TV-based restoration problem with l0-norm data fidelity. To effectively deal with the resulting non-convex non-smooth optimization problem, we first reformulate it as an equivalent biconvex Mathematical Program with Equilibrium Constraints (MPEC), and then solve it using a proximal Alternating Direction Method of Multipliers (PADMM). Our l0TV-PADMM method finds a desirable solution to the original l0-norm optimization problem and is proven to be convergent under mild conditions. We apply l0TV-PADMM to the problems of image denoising and deblurring in the presence of impulse noise. Our extensive experiments demonstrate that l0TV-PADMM outperforms state-of-the-art image restoration methods.

Photovoltaic Retinal Prosthesis for Restoring Sight to Patients Blinded by Retinal Injury or Degeneration

Science.gov (United States)

2016-02-01

We explored two boundary conditions for the stimulating and return electrodes: (1) When surface of each electrode was assumed equipotential , the...Stanford Nanofabrication Facility (SNF) using Surface Technology Systems (STS) PECVD. The precursors were SiH4 and NH3 (40:33.5 ratio of SiH4/NH3) at a... surface coating of retinal prostheses by PECVD at SNF (Plasma- Therm Shuttlelock SLR-730-PECVD). This tool used a capacitive-coupled plasma with

Parallel detecting super-resolution microscopy using correlation based image restoration

Science.gov (United States)

Yu, Zhongzhi; Liu, Shaocong; Zhu, Dazhao; Kuang, Cuifang; Liu, Xu

2017-12-01

A novel approach to achieve the image restoration is proposed in which each detector's relative position in the detector array is no longer a necessity. We can identify each detector's relative location by extracting a certain area from one of the detector's image and scanning it on other detectors' images. According to this location, we can generate the point spread functions (PSF) for each detector and perform deconvolution for image restoration. Equipped with this method, the microscope with discretionally designed detector array can be easily constructed without the concern of exact relative locations of detectors. The simulated results and experimental results show the total improvement in resolution with a factor of 1.7 compared to conventional confocal fluorescence microscopy. With the significant enhancement in resolution and easiness for application of this method, this novel method should have potential for a wide range of application in fluorescence microscopy based on parallel detecting.

Microstructure Images Restoration of Metallic Materials Based upon KSVD and Smoothing Penalty Sparse Representation Approach.

Science.gov (United States)

Li, Qing; Liang, Steven Y

2018-04-20

Microstructure images of metallic materials play a significant role in industrial applications. To address image degradation problem of metallic materials, a novel image restoration technique based on K-means singular value decomposition (KSVD) and smoothing penalty sparse representation (SPSR) algorithm is proposed in this work, the microstructure images of aluminum alloy 7075 (AA7075) material are used as examples. To begin with, to reflect the detail structure characteristics of the damaged image, the KSVD dictionary is introduced to substitute the traditional sparse transform basis (TSTB) for sparse representation. Then, due to the image restoration, modeling belongs to a highly underdetermined equation, and traditional sparse reconstruction methods may cause instability and obvious artifacts in the reconstructed images, especially reconstructed image with many smooth regions and the noise level is strong, thus the SPSR (here, q = 0.5) algorithm is designed to reconstruct the damaged image. The results of simulation and two practical cases demonstrate that the proposed method has superior performance compared with some state-of-the-art methods in terms of restoration performance factors and visual quality. Meanwhile, the grain size parameters and grain boundaries of microstructure image are discussed before and after they are restored by proposed method.

Restoration of uneven illumination in light sheet microscopy images.

Science.gov (United States)

Uddin, Mohammad Shorif; Lee, Hwee Kuan; Preibisch, Stephan; Tomancak, Pavel

2011-08-01

Light microscopy images suffer from poor contrast due to light absorption and scattering by the media. The resulting decay in contrast varies exponentially across the image along the incident light path. Classical space invariant deconvolution approaches, while very effective in deblurring, are not designed for the restoration of uneven illumination in microscopy images. In this article, we present a modified radiative transfer theory approach to solve the contrast degradation problem of light sheet microscopy (LSM) images. We confirmed the effectiveness of our approach through simulation as well as real LSM images.

PIZZARO: Forensic analysis and restoration of image and video data

Czech Academy of Sciences Publication Activity Database

Kamenický, Jan; Bartoš, Michal; Flusser, Jan; Mahdian, Babak; Kotera, Jan; Novozámský, Adam; Saic, Stanislav; Šroubek, Filip; Šorel, Michal; Zita, Aleš; Zitová, Barbara; Šíma, Z.; Švarc, P.; Hořínek, J.

2016-01-01

Roč. 264, č. 1 (2016), s. 153-166 ISSN 0379-0738 R&D Projects: GA MV VG20102013064; GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : Image forensic analysis * Image restoration * Image tampering detection * Image source identification Subject RIV: JD - Computer Applications, Robotics Impact factor: 1.989, year: 2016 http://library.utia.cas.cz/separaty/2016/ZOI/kamenicky-0459504.pdf

Ultra-wide field imaging system and traditional retinal examinations for screening fundus changes after cataract surgery.

Science.gov (United States)

Peng, Jie; Zhang, Qi; Jin, Hai-Ying; Lu, Wu-Yi; Zhao, Pei-Quan

2016-01-01

To compare the results of non-mydriatic ultra-wide field imaging system, mydriatic slit-lamp lens (Volk +90 D) and mydriatic Goldmann three-mirror contact lens examinations in screening fundus lesions among patients after cataract surgery. Non-mydriatic images were obtained with an Optomap panoramic 200Tx (Optomap 200Tx) 3d after surgery and graded by a blinded ophthalmologist. A mydriatic slit-lamp lens examination was performed by another blinded retinal specialist on the same day. A third blinded retinal specialist examined patients two weeks after surgery using a Goldmann three-mirror contact lens. In total, 160 patients (184 eyes) were examined, and 66, 69, and 75 cases of retinal lesion(s) were identified using the Optomap 200Tx, slit-lamp lens, and Goldmann three-mirror contact lens, respectively. In 13 cases, fundus changes were sight-threatening. The results obtained by Optomap 200Tx examination and by mydriatic slit-lamp lens examination have good consistency (P=0.375, Kappa=0.942). The mydriatic Goldmann three-mirror lens examination revealed more fundus lesions but are consistent with Optomap 200Tx (P=0.004, Kappa=0.897) and mydriatic slit-lamp lens examination (P=0.031, Kappa=0.932). Early post-operative fundus screening in cataract patients is extremely important and necessary to prevent further vision loss. Wide-field imaging is a feasible and convenient tool for fundus examination that can be used as a primary screening method among patients after cataract surgery.

Two-photon excited autofluorescence imaging of human retinal pigment epithelial cells

Science.gov (United States)

Han, Meng; Blindewald-Wittich, Almut; Holz, Frank G.; Giese, Günter; Niemz, Markolf H.; Snyder, Sarah; Sun, Hui; Yu, Jiayi; Agopov, Michael; La Schiazza, Olivier; Bille, Josef F.

2006-01-01

Degeneration of retinal pigment epithelial (RPE) cells severely impairs the visual function of retina photoreceptors. However, little is known about the events that trigger the death of RPE cells at the subcellular level. Two-photon excited autofluorescence (TPEF) imaging of RPE cells proves to be well suited to investigate both the morphological and the spectral characteristics of the human RPE cells. The dominant fluorophores of autofluorescence derive from lipofuscin (LF) granules that accumulate in the cytoplasm of the RPE cells with increasing age. Spectral TPEF imaging reveals the existence of abnormal LF granules with blue shifted autofluorescence in RPE cells of aging patients and brings new insights into the complicated composition of the LF granules. Based on a proposed two-photon laser scanning ophthalmoscope, TPEF imaging of the living retina may be valuable for diagnostic and pathological studies of age related eye diseases.

Zone specific fractal dimension of retinal images as predictor of stroke incidence.

Science.gov (United States)

Aliahmad, Behzad; Kumar, Dinesh Kant; Hao, Hao; Unnikrishnan, Premith; Che Azemin, Mohd Zulfaezal; Kawasaki, Ryo; Mitchell, Paul

2014-01-01

Fractal dimensions (FDs) are frequently used for summarizing the complexity of retinal vascular. However, previous techniques on this topic were not zone specific. A new methodology to measure FD of a specific zone in retinal images has been developed and tested as a marker for stroke prediction. Higuchi's fractal dimension was measured in circumferential direction (FDC) with respect to optic disk (OD), in three concentric regions between OD boundary and 1.5 OD diameter from its margin. The significance of its association with future episode of stroke event was tested using the Blue Mountain Eye Study (BMES) database and compared against spectrum fractal dimension (SFD) and box-counting (BC) dimension. Kruskal-Wallis analysis revealed FDC as a better predictor of stroke (H = 5.80, P = 0.016, α = 0.05) compared with SFD (H = 0.51, P = 0.475, α = 0.05) and BC (H = 0.41, P = 0.520, α = 0.05) with overall lower median value for the cases compared to the control group. This work has shown that there is a significant association between zone specific FDC of eye fundus images with future episode of stroke while this difference is not significant when other FD methods are employed.

Fully Automated Robust System to Detect Retinal Edema, Central Serous Chorioretinopathy, and Age Related Macular Degeneration from Optical Coherence Tomography Images

Directory of Open Access Journals (Sweden)

Samina Khalid

2017-01-01

Full Text Available Maculopathy is the excessive damage to macula that leads to blindness. It mostly occurs due to retinal edema (RE, central serous chorioretinopathy (CSCR, or age related macular degeneration (ARMD. Optical coherence tomography (OCT imaging is the latest eye testing technique that can detect these syndromes in early stages. Many researchers have used OCT images to detect retinal abnormalities. However, to the best of our knowledge, no research that presents a fully automated system to detect all of these macular syndromes is reported. This paper presents the world’s first ever decision support system to automatically detect RE, CSCR, and ARMD retinal pathologies and healthy retina from OCT images. The automated disease diagnosis in our proposed system is based on multilayered support vector machines (SVM classifier trained on 40 labeled OCT scans (10 healthy, 10 RE, 10 CSCR, and 10 ARMD. After training, SVM forms an accurate decision about the type of retinal pathology using 9 extracted features. We have tested our proposed system on 2819 OCT scans (1437 healthy, 640 RE, and 742 CSCR of 502 patients from two different datasets and our proposed system correctly diagnosed 2817/2819 subjects with the accuracy, sensitivity, and specificity ratings of 99.92%, 100%, and 99.86%, respectively.

Automatic classification of retinal three-dimensional optical coherence tomography images using principal component analysis network with composite kernels.

Science.gov (United States)

Fang, Leyuan; Wang, Chong; Li, Shutao; Yan, Jun; Chen, Xiangdong; Rabbani, Hossein

2017-11-01

We present an automatic method, termed as the principal component analysis network with composite kernel (PCANet-CK), for the classification of three-dimensional (3-D) retinal optical coherence tomography (OCT) images. Specifically, the proposed PCANet-CK method first utilizes the PCANet to automatically learn features from each B-scan of the 3-D retinal OCT images. Then, multiple kernels are separately applied to a set of very important features of the B-scans and these kernels are fused together, which can jointly exploit the correlations among features of the 3-D OCT images. Finally, the fused (composite) kernel is incorporated into an extreme learning machine for the OCT image classification. We tested our proposed algorithm on two real 3-D spectral domain OCT (SD-OCT) datasets (of normal subjects and subjects with the macular edema and age-related macular degeneration), which demonstrated its effectiveness. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Color correction with blind image restoration based on multiple images using a low-rank model

Science.gov (United States)

Li, Dong; Xie, Xudong; Lam, Kin-Man

2014-03-01

We present a method that can handle the color correction of multiple photographs with blind image restoration simultaneously and automatically. We prove that the local colors of a set of images of the same scene exhibit the low-rank property locally both before and after a color-correction operation. This property allows us to correct all kinds of errors in an image under a low-rank matrix model without particular priors or assumptions. The possible errors may be caused by changes of viewpoint, large illumination variations, gross pixel corruptions, partial occlusions, etc. Furthermore, a new iterative soft-segmentation method is proposed for local color transfer using color influence maps. Due to the fact that the correct color information and the spatial information of images can be recovered using the low-rank model, more precise color correction and many other image-restoration tasks-including image denoising, image deblurring, and gray-scale image colorizing-can be performed simultaneously. Experiments have verified that our method can achieve consistent and promising results on uncontrolled real photographs acquired from the Internet and that it outperforms current state-of-the-art methods.

Performance Evaluation of State-of-the-Art Local Feature Detectors and Descriptors in the Context of Longitudinal Registration of Retinal Images.

Science.gov (United States)

Saha, Sajib K; Xiao, Di; Frost, Shaun; Kanagasingam, Yogesan

2018-02-17

In this paper we systematically evaluate the performance of several state-of-the-art local feature detectors and descriptors in the context of longitudinal registration of retinal images. Longitudinal (temporal) registration facilitates to track the changes in the retina that has happened over time. A wide number of local feature detectors and descriptors exist and many of them have already applied for retinal image registration, however, no comparative evaluation has been made so far to analyse their respective performance. In this manuscript we evaluate the performance of the widely known and commonly used detectors such as Harris, SIFT, SURF, BRISK, and bifurcation and cross-over points. As of descriptors SIFT, SURF, ALOHA, BRIEF, BRISK and PIIFD are used. Longitudinal retinal image datasets containing a total of 244 images are used for the experiment. The evaluation reveals some potential findings including more robustness of SURF and SIFT keypoints than the commonly used bifurcation and cross-over points, when detected on the vessels. SIFT keypoints can be detected with a reliability of 59% for without pathology images and 45% for with pathology images. For SURF keypoints these values are respectively 58% and 47%. ALOHA descriptor is best suited to describe SURF keypoints, which ensures an overall matching accuracy, distinguishability of 83%, 93% and 78%, 83% for without pathology and with pathology images respectively.

Hardware architecture design of image restoration based on time-frequency domain computation

Science.gov (United States)

Wen, Bo; Zhang, Jing; Jiao, Zipeng

2013-10-01

The image restoration algorithms based on time-frequency domain computation is high maturity and applied widely in engineering. To solve the high-speed implementation of these algorithms, the TFDC hardware architecture is proposed. Firstly, the main module is designed, by analyzing the common processing and numerical calculation. Then, to improve the commonality, the iteration control module is planed for iterative algorithms. In addition, to reduce the computational cost and memory requirements, the necessary optimizations are suggested for the time-consuming module, which include two-dimensional FFT/IFFT and the plural calculation. Eventually, the TFDC hardware architecture is adopted for hardware design of real-time image restoration system. The result proves that, the TFDC hardware architecture and its optimizations can be applied to image restoration algorithms based on TFDC, with good algorithm commonality, hardware realizability and high efficiency.

Technical factors influencing cone packing density estimates in adaptive optics flood illuminated retinal images.

Directory of Open Access Journals (Sweden)

Marco Lombardo

Full Text Available PURPOSE: To investigate the influence of various technical factors on the variation of cone packing density estimates in adaptive optics flood illuminated retinal images. METHODS: Adaptive optics images of the photoreceptor mosaic were obtained in fifteen healthy subjects. The cone density and Voronoi diagrams were assessed in sampling windows of 320×320 µm, 160×160 µm and 64×64 µm at 1.5 degree temporal and superior eccentricity from the preferred locus of fixation (PRL. The technical factors that have been analyzed included the sampling window size, the corrected retinal magnification factor (RMFcorr, the conversion from radial to linear distance from the PRL, the displacement between the PRL and foveal center and the manual checking of cone identification algorithm. Bland-Altman analysis was used to assess the agreement between cone density estimated within the different sampling window conditions. RESULTS: The cone density declined with decreasing sampling area and data between areas of different size showed low agreement. A high agreement was found between sampling areas of the same size when comparing density calculated with or without using individual RMFcorr. The agreement between cone density measured at radial and linear distances from the PRL and between data referred to the PRL or the foveal center was moderate. The percentage of Voronoi tiles with hexagonal packing arrangement was comparable between sampling areas of different size. The boundary effect, presence of any retinal vessels, and the manual selection of cones missed by the automated identification algorithm were identified as the factors influencing variation of cone packing arrangements in Voronoi diagrams. CONCLUSIONS: The sampling window size is the main technical factor that influences variation of cone density. Clear identification of each cone in the image and the use of a large buffer zone are necessary to minimize factors influencing variation of Voronoi

Fast nonconvex nonsmooth minimization methods for image restoration and reconstruction.

Science.gov (United States)

Nikolova, Mila; Ng, Michael K; Tam, Chi-Pan

2010-12-01

Nonconvex nonsmooth regularization has advantages over convex regularization for restoring images with neat edges. However, its practical interest used to be limited by the difficulty of the computational stage which requires a nonconvex nonsmooth minimization. In this paper, we deal with nonconvex nonsmooth minimization methods for image restoration and reconstruction. Our theoretical results show that the solution of the nonconvex nonsmooth minimization problem is composed of constant regions surrounded by closed contours and neat edges. The main goal of this paper is to develop fast minimization algorithms to solve the nonconvex nonsmooth minimization problem. Our experimental results show that the effectiveness and efficiency of the proposed algorithms.

Automated drusen detection in retinal images using analytical modelling algorithms

Directory of Open Access Journals (Sweden)

Manivannan Ayyakkannu

2011-07-01

Full Text Available Abstract Background Drusen are common features in the ageing macula associated with exudative Age-Related Macular Degeneration (ARMD. They are visible in retinal images and their quantitative analysis is important in the follow up of the ARMD. However, their evaluation is fastidious and difficult to reproduce when performed manually. Methods This article proposes a methodology for Automatic Drusen Deposits Detection and quantification in Retinal Images (AD3RI by using digital image processing techniques. It includes an image pre-processing method to correct the uneven illumination and to normalize the intensity contrast with smoothing splines. The drusen detection uses a gradient based segmentation algorithm that isolates drusen and provides basic drusen characterization to the modelling stage. The detected drusen are then fitted by Modified Gaussian functions, producing a model of the image that is used to evaluate the affected area. Twenty two images were graded by eight experts, with the aid of a custom made software and compared with AD3RI. This comparison was based both on the total area and on the pixel-to-pixel analysis. The coefficient of variation, the intraclass correlation coefficient, the sensitivity, the specificity and the kappa coefficient were calculated. Results The ground truth used in this study was the experts' average grading. In order to evaluate the proposed methodology three indicators were defined: AD3RI compared to the ground truth (A2G; each expert compared to the other experts (E2E and a standard Global Threshold method compared to the ground truth (T2G. The results obtained for the three indicators, A2G, E2E and T2G, were: coefficient of variation 28.8 %, 22.5 % and 41.1 %, intraclass correlation coefficient 0.92, 0.88 and 0.67, sensitivity 0.68, 0.67 and 0.74, specificity 0.96, 0.97 and 0.94, and kappa coefficient 0.58, 0.60 and 0.49, respectively. Conclusions The gradings produced by AD3RI obtained an agreement

Restoration of longitudinal laser tomography target image from inhomogeneous medium degradation under common conditions.

Science.gov (United States)

Yi, WenJun; Wang, Ping; Fu, MeiCheng; Tan, JiChun; Zhu, Jubo; Li, XiuJian

2017-07-10

In order to overcome the shortages of the target image restoration method for longitudinal laser tomography using self-calibration, a more general restoration method through backscattering medium images associated with prior parameters is developed for common conditions. The system parameters are extracted from pre-calibration, and the LIDAR ratio is estimated according to the medium types. Assisted by these prior parameters, the degradation caused by inhomogeneous turbid media can be established with the backscattering medium images, which can further be used for removal of the interferences of turbid media. The results of simulations and experiments demonstrate that the proposed image restoration method can effectively eliminate the inhomogeneous interferences of turbid media and achieve exactly the reflectivity distribution of targets behind inhomogeneous turbid media. Furthermore, the restoration method can work beyond the limitation of the previous method that only works well under the conditions of localized turbid attenuations and some types of targets with fairly uniform reflectivity distributions.

Differentiation of Pluripotent Stem Cells to Retinal Pigment Epithelial Cells: An Approach Toward Retinal Degenerative Diseases Treatment

Directory of Open Access Journals (Sweden)

Maryam Parvini

2013-10-01

Full Text Available Pluripotent stem cells as the cells with a capacity for self-renewal and differentiation into various specificcell types have been highly regarded in regenerative medicine studies. To repair the eye disease damages, thedifferentiation into retinal pigment epithelial cells of pluripotent stem cells has gained great importance inrecent decades because the inappropriate function of these cells is the main cause of degenerative diseases suchas the age-related macular degeneration. Millions of people in the world suffer this disease.To restore the damaged cells and, finally, to improve the vision, numerous studies have been conducted on usingpluripotent stem cells, their differentiation into retinal pigment epithelial cells, and finally, their applicationin cell therapy. Based on this, many researchers have attempted to produce highly efficient retinal pigmentepithelial cells, such that they show a proper function after transplant, along with the host cells. In this reviewarticle, the importance and the role of pigment epithelial cells, as well as, the studies on the in vitro productionof these cells were examined

Retinitis pigmentosa

Directory of Open Access Journals (Sweden)

Hamel Christian

2006-10-01

Full Text Available Abstract Retinitis pigmentosa (RP is an inherited retinal dystrophy caused by the loss of photoreceptors and characterized by retinal pigment deposits visible on fundus examination. Prevalence of non syndromic RP is approximately 1/4,000. The most common form of RP is a rod-cone dystrophy, in which the first symptom is night blindness, followed by the progressive loss in the peripheral visual field in daylight, and eventually leading to blindness after several decades. Some extreme cases may have a rapid evolution over two decades or a slow progression that never leads to blindness. In some cases, the clinical presentation is a cone-rod dystrophy, in which the decrease in visual acuity predominates over the visual field loss. RP is usually non syndromic but there are also many syndromic forms, the most frequent being Usher syndrome. To date, 45 causative genes/loci have been identified in non syndromic RP (for the autosomal dominant, autosomal recessive, X-linked, and digenic forms. Clinical diagnosis is based on the presence of night blindness and peripheral visual field defects, lesions in the fundus, hypovolted electroretinogram traces, and progressive worsening of these signs. Molecular diagnosis can be made for some genes, but is not usually performed due to the tremendous genetic heterogeneity of the disease. Genetic counseling is always advised. Currently, there is no therapy that stops the evolution of the disease or restores the vision, so the visual prognosis is poor. The therapeutic approach is restricted to slowing down the degenerative process by sunlight protection and vitaminotherapy, treating the complications (cataract and macular edema, and helping patients to cope with the social and psychological impact of blindness. However, new therapeutic strategies are emerging from intensive research (gene therapy, neuroprotection, retinal prosthesis.

Image restoration by the method of convex projections: part 2 applications and numerical results.

Science.gov (United States)

Sezan, M I; Stark, H

1982-01-01

The image restoration theory discussed in a previous paper by Youla and Webb [1] is applied to a simulated image and the results compared with the well-known method known as the Gerchberg-Papoulis algorithm. The results show that the method of image restoration by projection onto convex sets, by providing a convenient technique for utilizing a priori information, performs significantly better than the Gerchberg-Papoulis method.

Parafoveal retinal cone mosaic imaging in children with ultra-compact switchable SLO/OCT handheld probe (Conference Presentation)

Science.gov (United States)

LaRocca, Francesco; Nankivil, Derek; DuBose, Theodore B.; Toth, Cynthia A.; Farsiu, Sina; Izatt, Joseph A.

2016-03-01

In vivo photoreceptor imaging has enhanced the way vision scientists and ophthalmologists understand the retinal structure, function, and etiology of numerous retinal pathologies. However, the complexity and large footprint of current systems capable of resolving photoreceptors has limited imaging to patients who are able to sit in an upright position and fixate for several minutes. Unfortunately, this excludes an important fraction of patients including bedridden patients, small children, and infants. Here, we show that our dual-modality, high-resolution handheld probe with a weight of only 94 g is capable of visualizing photoreceptors in supine children. Our device utilizes a microelectromechanical systems (MEMS) scanner and a novel telescope design to achieve over an order of magnitude reduction in size compared to similar systems. The probe has a 7° field of view and a lateral resolution of 8 µm. The optical coherence tomography (OCT) system has an axial resolution of 7 µm and a sensitivity of 101 dB. High definition scanning laser ophthalmoscopy (SLO) and OCT images were acquired from children ranging from 14 months to 12 years of age with and without pathology during examination under anesthesia in the operating room. Parafoveal cone imaging was shown using the SLO arm of this device without adaptive optics using a 3° FOV for the first time in children under 4 years old. This work lays the foundation for pediatric research, which will improve understanding of retinal development, maldevelopment and early onset of diseases at the cellular level during the beginning stages of human growth.

Congenital Retinal Macrovessel and the Association of Retinal Venous Malformations With Venous Malformations of the Brain.

Science.gov (United States)

Pichi, Francesco; Freund, K Bailey; Ciardella, Antonio; Morara, Mariachiara; Abboud, Emad B; Ghazi, Nicola; Dackiw, Christine; Choudhry, Netan; Souza, Eduardo Cunha; Cunha, Leonardo Provetti; Arevalo, J Fernando; Liu, T Y Alvin; Wenick, Adam; He, Lingmin; Villarreal, Guadalupe; Neri, Piergiorgio; Sarraf, David

2018-04-01

Congenital retinal macrovessel (CRM) is a rarely reported venous malformation of the retina that is associated with venous anomalies of the brain. To study the multimodal imaging findings of a series of eyes with congenital retinal macrovessel and describe the systemic associations. In this cross-sectional multicenter study, medical records were retrospectively reviewed from 7 different retina clinics worldwide over a 10-year period (2007-2017). Patients with CRM, defined as an abnormal, large, macular vessel with a vascular distribution above and below the horizontal raphe, were identified. Data were analyzed from December 2016 to August 2017. Clinical information and multimodal retinal imaging findings were collected and studied. Pertinent systemic information, including brain magnetic resonance imaging findings, was also noted if available. Of the 49 included patients, 32 (65%) were female, and the mean (SD) age at onset was 44.0 (20.9) years. A total of 49 eyes from 49 patients were studied. Macrovessel was unilateral in all patients. Color fundus photography illustrated a large aberrant dilated and tortuous retinal vein in all patients. Early-phase frames of fluorescein angiography further confirmed the venous nature of the macrovessel in 40 of 40 eyes. Optical coherence tomography angiography, available in 17 eyes (35%), displayed microvascular capillary abnormalities around the CRM, which were more evident in the deep capillary plexus. Of the 49 patients with CRM, 39 (80%) did not illustrate any evidence of ophthalmic complications. Ten patients (20%) presented with retinal complications, typically an incidental association with CRM. Twelve patients (24%) were noted to have venous malformations of the brain with associated magnetic resonance imaging. Of these, location of the venous anomaly in the brain was ipsilateral to the CRM in 10 patients (83%) and contralateral in 2 patients (17%), mainly located in the frontal lobe in 9 patients (75%). Our study has

Contribution to restoration of degraded images by a space-variant system: use of an a priori model of the image

International Nuclear Information System (INIS)

Barakat, Valerie

1998-01-01

Imaging systems often present shift-variant point spread functions which are usually approximated by shift-invariant ones, in order to simplify the restoration problem. The aim of this thesis is to show that, if this shift-variant degradation is taken into account, it may increase strongly the quality of restoration. The imaging system is a pinhole, used to acquire images of high energy beams. Three restoration methods have been studied and compared: the Tikhonov-Miller regularization, the Markov-fields and the Maximum-Entropy methods. These methods are based on the incorporation of an a priori knowledge into the restoration process, to achieve stability of the solution. An improved restoration method is proposed: this approach is based on the Tikhonov-Miller regularization, combined with an a priori model of the solution. The idea of such a model is to express local characteristics to be reconstructed. The concept of parametric models described by a set of parameters (shape of the object, amplitude values,...) is used. A parametric optimization is used to find the optimal estimation of parameters close to the correct a priori information data of the expected solution. Several criteria have been proposed to measure the restoration quality. (author) [fr

Image restoration by Wiener filtering in the presence of signal-dependent noise.

Science.gov (United States)

Kondo, K; Ichioka, Y; Suzuki, T

1977-09-01

An optimum filter to restore the degraded image due to blurring and the signal-dependent noise is obtained on the basis of the theory of Wiener filtering. Computer simulations of image restoration using signal-dependent noise models are carried out. It becomes clear that the optimum filter, which makes use of a priori information on the signal-dependent nature of the noise and the spectral density of the signal and the noise showing significant spatial correlation, is potentially advantageous.

An Automated System for the Detection and Classification of Retinal Changes Due to Red Lesions in Longitudinal Fundus Images

NARCIS (Netherlands)

Adal, K.M.; Van Etten, Peter G.; Martinez, Jose P; Rouwen, Kenneth W.; Vermeer, K.A.; van Vliet, L.J.

People with diabetes mellitus need annual screening to check for the development of diabetic retinopathy. Tracking small retinal changes due to early diabetic retinopathy lesions in longitudinal fundus image sets is challenging due to intra- and inter-visit variability in illumination and image

Analysis of visual appearance of retinal nerve fibers in high resolution fundus images: a study on normal subjects.

Science.gov (United States)

Kolar, Radim; Tornow, Ralf P; Laemmer, Robert; Odstrcilik, Jan; Mayer, Markus A; Gazarek, Jiri; Jan, Jiri; Kubena, Tomas; Cernosek, Pavel

2013-01-01

The retinal ganglion axons are an important part of the visual system, which can be directly observed by fundus camera. The layer they form together inside the retina is the retinal nerve fiber layer (RNFL). This paper describes results of a texture RNFL analysis in color fundus photographs and compares these results with quantitative measurement of RNFL thickness obtained from optical coherence tomography on normal subjects. It is shown that local mean value, standard deviation, and Shannon entropy extracted from the green and blue channel of fundus images are correlated with corresponding RNFL thickness. The linear correlation coefficients achieved values 0.694, 0.547, and 0.512 for respective features measured on 439 retinal positions in the peripapillary area from 23 eyes of 15 different normal subjects.

Restoration of the analytically reconstructed OpenPET images by the method of convex projections

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Tashima, Hideaki; Murayama, Hideo; Yamaya, Taiga [National Institute of Radiological Sciences, Chiba (Japan); Katsunuma, Takayuki; Suga, Mikio [Chiba Univ. (Japan). Graduate School of Engineering; Kinouchi, Shoko [National Institute of Radiological Sciences, Chiba (Japan); Chiba Univ. (Japan). Graduate School of Engineering; Obi, Takashi [Tokyo Institute of Technology (Japan). Interdisciplinary Graduate School of Science and Engineering; Kudo, Hiroyuki [Tsukuba Univ. (Japan). Graduate School of Systems and Information Engineering

2011-07-01

We have proposed the OpenPET geometry which has gaps between detector rings and physically opened field-of-view. The image reconstruction of the OpenPET is classified into an incomplete problem because it does not satisfy the Orlov's condition. Even so, the simulation and experimental studies have shown that applying iterative methods such as the maximum likelihood expectation maximization (ML-EM) algorithm successfully reconstruct images in the gap area. However, the imaging process of the iterative methods in the OpenPET imaging is not clear. Therefore, the aim of this study is to analytically analyze the OpenPET imaging and estimate implicit constraints involved in the iterative methods. To apply explicit constraints in the OpenPET imaging, we used the method of convex projections for restoration of the images reconstructed by the analytical way in which low-frequency components are lost. Numerical simulations showed that the similar restoration effects are involved both in the ML-EM and the method of convex projections. Therefore, the iterative methods have advantageous effect of restoring lost frequency components of the OpenPET imaging. (orig.)

Superresolution restoration of an image sequence: adaptive filtering approach.

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Elad, M; Feuer, A

1999-01-01

This paper presents a new method based on adaptive filtering theory for superresolution restoration of continuous image sequences. The proposed methodology suggests least squares (LS) estimators which adapt in time, based on adaptive filters, least mean squares (LMS) or recursive least squares (RLS). The adaptation enables the treatment of linear space and time-variant blurring and arbitrary motion, both of them assumed known. The proposed new approach is shown to be of relatively low computational requirements. Simulations demonstrating the superresolution restoration algorithms are presented.

The Tonya Harding Controversy: An Analysis of Image Restoration Strategies.

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Benoit, William L.; Hanczor, Robert S.

1994-01-01

Analyzes Tonya Harding's defense of her image in "Eye to Eye with Connie Chung," applying the theory of image restoration discourse. Finds that the principal strategies employed in her behalf were bolstering, denial, and attacking her accuser, but that these strategies were not developed very effectively in this instance. (SR)

SDOCT imaging to identify macular pathology in patients diagnosed with diabetic maculopathy by a digital photographic retinal screening programme.

Directory of Open Access Journals (Sweden)

Sarah Mackenzie

Full Text Available INTRODUCTION: Diabetic macular edema (DME is an important cause of vision loss. England has a national systematic photographic retinal screening programme to identify patients with diabetic eye disease. Grading retinal photographs according to this national protocol identifies surrogate markers for DME. We audited a care pathway using a spectral-domain optical coherence tomography (SDOCT clinic to identify macular pathology in this subset of patients. METHODS: A prospective audit was performed of patients referred from screening with mild to moderate non-proliferative diabetic retinopathy (R1 and surrogate markers for diabetic macular edema (M1 attending an SDOCT clinic. The SDOCT images were graded by an ophthalmologist as SDOCT positive, borderline or negative. SDOCT positive patients were referred to the medical retina clinic. SDOCT negative and borderline patients were further reviewed in the SDOCT clinic in 6 months. RESULTS: From a registered screening population of 17 551 patients with diabetes mellitus, 311 patients met the inclusion criteria between (March 2008 and September 2009. We analyzed images from 311 patients' SDOCT clinic episodes. There were 131 SDOCT negative and 12 borderline patients booked for revisit in the OCT clinic. Twenty-four were referred back to photographic screening for a variety of reasons. A total of 144 were referred to ophthalmology with OCT evidence of definite macular pathology requiring review by an ophthalmologist. DISCUSSION: This analysis shows that patients with diabetes, mild to moderate non-proliferative diabetic retinopathy (R1 and evidence of diabetic maculopathy on non-stereoscopic retinal photographs (M1 have a 42.1% chance of having no macular edema on SDOCT imaging as defined by standard OCT definitions of DME when graded by a retinal specialist. SDOCT imaging is a useful adjunct to colour fundus photography in screening for referable diabetic maculopathy in our screening population.

Placement of a crystalline lens and intraocular lens: Retinal image quality.

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Siedlecki, Damian; Nowak, Jerzy; Zajac, Marek

2006-01-01

The influence of changes of both crystalline lens and intraocular lens (IOL) misalignment on the retinal image quality was investigated. The optical model of the eye used in investigations was the Liou-Brennan model, which is commonly considered as one of the most anatomically accurate. The original crystalline lens from this model was replaced with an IOL, made of rigid polymethylmethacrylate, in a way that recommend obligatory procedures. The modifications that were made both for crystalline lens and IOL were the longitudinal, the transversal, and the angular displacement.

Multi-characteristic opsin enabled vision restoration

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Wright, Weldon; Pradhan, Sanjay; Bhattacharya, Sulgana; Mahapatra, Vasu; Tripathy, Ashutosh; Gajjeraman, Sivakumar; Mohanty, Samarendra

2017-02-01

Photodegenerative retinal diseases such as retinitis pigmentosa (RP) and dry age related macular degeneration (dry- AMD) lead to loss of vision in millions of individuals. Currently, no surgical or medical treatment is available though optogenetic therapies are in clinical development. Here, we demonstrate vision restoration using Multi- Characteristics Opsin (MCO1) in animal models with photo-degenerated retina. MCO1 is reliably delivered to specific retinal cells via intravitreal injection of Adeno-Associated Virus, leading to significant improvement in visually guided behavior conducted using a radial-arm water maze. The time to reach platform significantly reduced after delivery of MCO1. Notably, the improvement in visually guided behavior was observed even at light intensity levels orders of magnitude lower than that required for Channelrhodopsin-2 opsin. Chronic light exposure study showed that chronic light exposure did not compromise viability of vMCO1-treated retina. Safe virus-mediated MCO1-delivery has potential for effective gene therapy of diverse retinal degenerations in patients.

Multimodal imaging of central retinal disease progression in a 2 year mean follow up of Retinitis Pigmentosa

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Sujirakul, Tharikarn; Lin, Michael K.; Duong, Jimmy; Wei, Ying; Lopez-Pintado, Sara; Tsang, Stephen H.

2015-01-01

Purpose To determine the rate of progression and optimal follow up time in patients with advanced stage retinitis pigmentosa (RP) comparing the use of fundus autofluorescence imaging and spectral domain optical coherence tomography. Design Retrospective analysis of progression rate. Methods Longitudinal imaging follow up in 71 patients with retinitis pigmentosa was studied using the main outcome measurements of hyperautofluoresent ring horizontal diameter and vertical diameter along with ellipsoid zone line width from spectral domain optical coherence tomography. Test-retest reliability and the rate of progression were calculated. The interaction between the progression rates was tested for sex, age, mode of inheritance, and baseline measurement size. Symmetry of left and right eye progression rate was also tested. Results Significant progression was observed in >75% of patients during the 2 year mean follow up. The mean annual progression rates of ellipsoid zone line, and hyperautofluorescent ring horizontal diameter and vertical diameter were 0.45° (4.9%), 0.51° (4.1%), and 0.42° (4.0%), respectively. The e llipsoid zone line width, and hyperautofluorescent ring horizontal diameter and vertical diameter had low test-retest variabilities of 8.9%, 9.5% and 9.6%, respectively. This study is the first to demonstrate asymmetrical structural progression rate between right and left eye, which was found in 19% of patients. The rate of progression was significantly slower as the disease approached the fovea, supporting the theory that RP progresses in an exponential fashion. No significant interaction between progression rate and patient age, sex, or mode of inheritance was observed. Conclusions Fundus autofluorescence and optical coherence tomography detect progression in patients with RP reliably and with strong correlation. These parameters may be useful alongside functional assessments as the outcome measurements for future therapeutic trials. Follow-up at 1 year

Automated detection of retinal whitening in malarial retinopathy

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Joshi, V.; Agurto, C.; Barriga, S.; Nemeth, S.; Soliz, P.; MacCormick, I.; Taylor, T.; Lewallen, S.; Harding, S.

2016-03-01

Cerebral malaria (CM) is a severe neurological complication associated with malarial infection. Malaria affects approximately 200 million people worldwide, and claims 600,000 lives annually, 75% of whom are African children under five years of age. Because most of these mortalities are caused by the high incidence of CM misdiagnosis, there is a need for an accurate diagnostic to confirm the presence of CM. The retinal lesions associated with malarial retinopathy (MR) such as retinal whitening, vessel discoloration, and hemorrhages, are highly specific to CM, and their detection can improve the accuracy of CM diagnosis. This paper will focus on development of an automated method for the detection of retinal whitening which is a unique sign of MR that manifests due to retinal ischemia resulting from CM. We propose to detect the whitening region in retinal color images based on multiple color and textural features. First, we preprocess the image using color and textural features of the CMYK and CIE-XYZ color spaces to minimize camera reflex. Next, we utilize color features of the HSL, CMYK, and CIE-XYZ channels, along with the structural features of difference of Gaussians. A watershed segmentation algorithm is used to assign each image region a probability of being inside the whitening, based on extracted features. The algorithm was applied to a dataset of 54 images (40 with whitening and 14 controls) that resulted in an image-based (binary) classification with an AUC of 0.80. This provides 88% sensitivity at a specificity of 65%. For a clinical application that requires a high specificity setting, the algorithm can be tuned to a specificity of 89% at a sensitivity of 82%. This is the first published method for retinal whitening detection and combining it with the detection methods for vessel discoloration and hemorrhages can further improve the detection accuracy for malarial retinopathy.

Mammographic image restoration using maximum entropy deconvolution

International Nuclear Information System (INIS)

Jannetta, A; Jackson, J C; Kotre, C J; Birch, I P; Robson, K J; Padgett, R

2004-01-01

An image restoration approach based on a Bayesian maximum entropy method (MEM) has been applied to a radiological image deconvolution problem, that of reduction of geometric blurring in magnification mammography. The aim of the work is to demonstrate an improvement in image spatial resolution in realistic noisy radiological images with no associated penalty in terms of reduction in the signal-to-noise ratio perceived by the observer. Images of the TORMAM mammographic image quality phantom were recorded using the standard magnification settings of 1.8 magnification/fine focus and also at 1.8 magnification/broad focus and 3.0 magnification/fine focus; the latter two arrangements would normally give rise to unacceptable geometric blurring. Measured point-spread functions were used in conjunction with the MEM image processing to de-blur these images. The results are presented as comparative images of phantom test features and as observer scores for the raw and processed images. Visualization of high resolution features and the total image scores for the test phantom were improved by the application of the MEM processing. It is argued that this successful demonstration of image de-blurring in noisy radiological images offers the possibility of weakening the link between focal spot size and geometric blurring in radiology, thus opening up new approaches to system optimization

A Probabilistic Framework for Content-Based Diagnosis of Retinal Disease

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Tobin Jr, Kenneth William [ORNL; Abdelrahman, Mohamed A [ORNL; Chaum, Edward [ORNL; Muthusamy Govindasamy, Vijaya Priya [ORNL; Karnowski, Thomas Paul [ORNL

2007-01-01

Diabetic retinopathy is the leading cause of blindness in the working age population around the world. Computer assisted analysis has the potential to assist in the early detection of diabetes by regular screening of large populations. The widespread availability of digital fundus cameras today is resulting in the accumulation of large image archives of diagnosed patient data that captures historical knowledge of retinal pathology. Through this research we are developing a content-based image retrieval method to verify our hypothesis that retinal pathology can be identified and quantified from visually similar retinal images in an image archive. We will present diagnostic results for specificity and sensitivity on a population of 395 fundus images representing the normal fundus and 14 stratified disease states.

Use of the Discrete Cosine Transform for the restoration of an image sequence

International Nuclear Information System (INIS)

Acheroy, M.P.J.

1985-01-01

The Discrete Cosine Transform (DCT) is recognized as an important tool for image compression techniques. Its use in image restoration is, however, not well known. It is the aim of this paper to provide a restoration method for a sequence of images using the DCT as well for the deblurring as for the noise reduction. It is shown that the DCT can play an interesting role in the deconvolution problem for linear imaging systems with finite, invariant and symmetric impulse response. It is further shown that the noise reduction can be performed onto an image sequence using a time adaptive Kalman filter in the domain of the Karhunen-Loeve transform which is approximated by the DCT

Image preprocessing for improving computational efficiency in implementation of restoration and superresolution algorithms.

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Sundareshan, Malur K; Bhattacharjee, Supratik; Inampudi, Radhika; Pang, Ho-Yuen

2002-12-10

Computational complexity is a major impediment to the real-time implementation of image restoration and superresolution algorithms in many applications. Although powerful restoration algorithms have been developed within the past few years utilizing sophisticated mathematical machinery (based on statistical optimization and convex set theory), these algorithms are typically iterative in nature and require a sufficient number of iterations to be executed to achieve the desired resolution improvement that may be needed to meaningfully perform postprocessing image exploitation tasks in practice. Additionally, recent technological breakthroughs have facilitated novel sensor designs (focal plane arrays, for instance) that make it possible to capture megapixel imagery data at video frame rates. A major challenge in the processing of these large-format images is to complete the execution of the image processing steps within the frame capture times and to keep up with the output rate of the sensor so that all data captured by the sensor can be efficiently utilized. Consequently, development of novel methods that facilitate real-time implementation of image restoration and superresolution algorithms is of significant practical interest and is the primary focus of this study. The key to designing computationally efficient processing schemes lies in strategically introducing appropriate preprocessing steps together with the superresolution iterations to tailor optimized overall processing sequences for imagery data of specific formats. For substantiating this assertion, three distinct methods for tailoring a preprocessing filter and integrating it with the superresolution processing steps are outlined. These methods consist of a region-of-interest extraction scheme, a background-detail separation procedure, and a scene-derived information extraction step for implementing a set-theoretic restoration of the image that is less demanding in computation compared with the

Confocal pore size measurement based on super-resolution image restoration.

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Liu, Dali; Wang, Yun; Qiu, Lirong; Mao, Xinyue; Zhao, Weiqian

2014-09-01

A confocal pore size measurement based on super-resolution image restoration is proposed to obtain a fast and accurate measurement for submicrometer pore size of nuclear track-etched membranes (NTEMs). This method facilitates the online inspection of the pore size evolution during etching. Combining confocal microscopy with super-resolution image restoration significantly improves the lateral resolution of the NTEM image, yields a reasonable circle edge-setting criterion of 0.2408, and achieves precise pore edge detection. Theoretical analysis shows that the minimum measuring diameter can reach 0.19 μm, and the root mean square of the residuals is only 1.4 nm. Edge response simulation and experiment reveal that the edge response of the proposed method is better than 80 nm. The NTEM pore size measurement results obtained by the proposed method agree well with that obtained by scanning electron microscopy.

Research on Adaptive Optics Image Restoration Algorithm by Improved Expectation Maximization Method

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Lijuan Zhang

2014-01-01

Full Text Available To improve the effect of adaptive optics images’ restoration, we put forward a deconvolution algorithm improved by the EM algorithm which joints multiframe adaptive optics images based on expectation-maximization theory. Firstly, we need to make a mathematical model for the degenerate multiframe adaptive optics images. The function model is deduced for the points that spread with time based on phase error. The AO images are denoised using the image power spectral density and support constraint. Secondly, the EM algorithm is improved by combining the AO imaging system parameters and regularization technique. A cost function for the joint-deconvolution multiframe AO images is given, and the optimization model for their parameter estimations is built. Lastly, the image-restoration experiments on both analog images and the real AO are performed to verify the recovery effect of our algorithm. The experimental results show that comparing with the Wiener-IBD or RL-IBD algorithm, our iterations decrease 14.3% and well improve the estimation accuracy. The model distinguishes the PSF of the AO images and recovers the observed target images clearly.

Multimodal Imaging of Disease-Associated Pigmentary Changes in Retinitis Pigmentosa

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Schuerch, Kaspar; Marsiglia, Marcela; Lee, Winston; Tsang, Stephen H.; Sparrow, Janet R.

2016-01-01

Purpose Using multiple imaging modalities we evaluated the changes in photoreceptor cells and RPE that are associated with bone spicule-shaped melanin pigmentation in retinitis pigmentosa (RP). Methods In a cohort of 60 RP patients, short-wavelength autofluorescence (SW-AF), near-infrared (NIR)-AF, NIR-reflectance (NIR-R), spectral domain optical coherence tomography (SD-OCT) and color fundus images were studied. Results Central AF rings were visible in both SW-AF and NIR-AF images. Bone spicule pigmentation was non-reflective in NIR-R, hypoautofluorescent with SW-AF and NIR-AF imaging and presented as intraretinal hyperreflective foci in SD-OCT images. In areas beyond the AF ring outer border, the photoreceptor ellipsoid zone (EZ) band was absent in SD-OCT scans and the visibility of choroidal vessels in SW-AF, NIR-AF and NIR-R images was indicative of reduced RPE pigmentation. Choroidal visibility was most pronounced in the zone approaching peripheral areas of bone spicule pigmentation; here RPE/Bruch’s membrane thinning became apparent in SD-OCT scans. Conclusions These findings are consistent with a process by which RPE cells vacate their monolayer and migrate into inner retina in response to photoreceptor cell degeneration. The remaining RPE spread, undergo thinning and consequently become less pigmented. An explanation for the absence of NIR-AF melanin signal in relation to bone spicule pigmentation is not forthcoming. PMID:28005673

Massive Bilateral Serous Retinal Detachment in a Case of Hypertensive Chorioretinopathy

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Luis Villalba-Pinto

2014-07-01

Full Text Available Introduction: Systemic high blood pressure is related to a variety of retinal manifestations. We present an atypical case of hypertensive chorioretinopathy with massive bilateral serous retinal detachment. Case Report: A 26-year-old male with a genitourinary malformation and secondary grade IV chronic kidney failure as well as high blood pressure complained of acute vision loss. Dilated fundus examination evidenced a bilateral serous retinal detachment with macular involvement. The patient was unresponsive to oral antihypertensive therapy and dialysis treatment. The serous retinal detachment progressively decreased after the restoration of dialysis and antihypertensive therapy. The final visual acuity was 0.50 in both eyes. Discussion: In cases of serous macular detachment, it is mandatory to rule out different systemic and ocular diseases. The presence of uncontrolled high blood pressure may produce aggressive bilateral retinal changes, thus hypertension must be under early and strict control in order to improve the visual outcomes.

Massive Bilateral Serous Retinal Detachment in a Case of Hypertensive Chorioretinopathy

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Villalba-Pinto, Luis; Hernández-Ortega, M. Ángeles; de los Mozos, F. Javier Lavid; Pascual-Camps, Isabel; Dolz-Marco, Rosa; Arevalo, J. Fernando; Gallego-Pinazo, Roberto

2014-01-01

Introduction Systemic high blood pressure is related to a variety of retinal manifestations. We present an atypical case of hypertensive chorioretinopathy with massive bilateral serous retinal detachment. Case Report A 26-year-old male with a genitourinary malformation and secondary grade IV chronic kidney failure as well as high blood pressure complained of acute vision loss. Dilated fundus examination evidenced a bilateral serous retinal detachment with macular involvement. The patient was unresponsive to oral antihypertensive therapy and dialysis treatment. The serous retinal detachment progressively decreased after the restoration of dialysis and antihypertensive therapy. The final visual acuity was 0.50 in both eyes. Discussion In cases of serous macular detachment, it is mandatory to rule out different systemic and ocular diseases. The presence of uncontrolled high blood pressure may produce aggressive bilateral retinal changes, thus hypertension must be under early and strict control in order to improve the visual outcomes. PMID:25120474

Critical Endothelial Regulation by LRP5 during Retinal Vascular Development

Science.gov (United States)

Huang, Wei; Li, Qing; Amiry-Moghaddam, Mahmood; Hokama, Madoka; Sardi, Sylvia H.; Nagao, Masashi; Warman, Matthew L.; Olsen, Bjorn R.

2016-01-01

Vascular abnormalities in the eye are the leading cause of many forms of inherited and acquired human blindness. Loss-of-function mutations in the Wnt-binding co-receptor LRP5 leads to aberrant ocular vascularization and loss of vision in genetic disorders such as osteoporosis-pseudoglioma syndrome. The canonical Wnt-β-catenin pathway is known to regulate retinal vascular development. However, it is unclear what precise role LPR5 plays in this process. Here, we show that loss of LRP5 function in mice causes retinal hypovascularization during development as well as retinal neovascularization in adulthood with disorganized and leaky vessels. Using a highly specific Flk1-CreBreier line for vascular endothelial cells, together with several genetic models, we demonstrate that loss of endothelium-derived LRP5 recapitulates the retinal vascular defects in Lrp5-/- mice. In addition, restoring LRP5 function only in endothelial cells in Lrp5-/- mice rescues their retinal vascular abnormalities. Furthermore, we show that retinal vascularization is regulated by LRP5 in a dosage dependent manner and does not depend on LRP6. Our study provides the first direct evidence that endothelium-derived LRP5 is both necessary and sufficient to mediate its critical role in the development and maintenance of retinal vasculature. PMID:27031698

Analysis of Visual Appearance of Retinal Nerve Fibers in High Resolution Fundus Images: A Study on Normal Subjects

Directory of Open Access Journals (Sweden)

Radim Kolar

2013-01-01

Full Text Available The retinal ganglion axons are an important part of the visual system, which can be directly observed by fundus camera. The layer they form together inside the retina is the retinal nerve fiber layer (RNFL. This paper describes results of a texture RNFL analysis in color fundus photographs and compares these results with quantitative measurement of RNFL thickness obtained from optical coherence tomography on normal subjects. It is shown that local mean value, standard deviation, and Shannon entropy extracted from the green and blue channel of fundus images are correlated with corresponding RNFL thickness. The linear correlation coefficients achieved values 0.694, 0.547, and 0.512 for respective features measured on 439 retinal positions in the peripapillary area from 23 eyes of 15 different normal subjects.

A comparative analysis of pre-processing techniques in colour retinal images

International Nuclear Information System (INIS)

Salvatelli, A; Bizai, G; Barbosa, G; Drozdowicz, B; Delrieux, C

2007-01-01

Diabetic retinopathy (DR) is a chronic disease of the ocular retina, which most of the times is only discovered when the disease is on an advanced stage and most of the damage is irreversible. For that reason, early diagnosis is paramount for avoiding the most severe consequences of the DR, of which complete blindness is not uncommon. Unsupervised or supervised image processing of retinal images emerges as a feasible tool for this diagnosis. The preprocessing stages are the key for any further assessment, since these images exhibit several defects, including non uniform illumination, sampling noise, uneven contrast due to pigmentation loss during sampling, and many others. Any feasible diagnosis system should work with images where these defects were compensated. In this work we analyze and test several correction techniques. Non uniform illumination is compensated using morphology and homomorphic filtering; uneven contrast is compensated using morphology and local enhancement. We tested our processing stages using Fuzzy C-Means, and local Hurst (self correlation) coefficient for unsupervised segmentation of the abnormal blood vessels. The results over a standard set of DR images are more than promising

A comparative analysis of pre-processing techniques in colour retinal images

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Salvatelli, A [Artificial Intelligence Group, Facultad de Ingenieria, Universidad Nacional de Entre Rios (Argentina); Bizai, G [Artificial Intelligence Group, Facultad de Ingenieria, Universidad Nacional de Entre Rios (Argentina); Barbosa, G [Artificial Intelligence Group, Facultad de Ingenieria, Universidad Nacional de Entre Rios (Argentina); Drozdowicz, B [Artificial Intelligence Group, Facultad de Ingenieria, Universidad Nacional de Entre Rios (Argentina); Delrieux, C [Electric and Computing Engineering Department, Universidad Nacional del Sur, Alem 1253, BahIa Blanca, (Partially funded by SECyT-UNS) (Argentina)], E-mail: claudio@acm.org

2007-11-15

Diabetic retinopathy (DR) is a chronic disease of the ocular retina, which most of the times is only discovered when the disease is on an advanced stage and most of the damage is irreversible. For that reason, early diagnosis is paramount for avoiding the most severe consequences of the DR, of which complete blindness is not uncommon. Unsupervised or supervised image processing of retinal images emerges as a feasible tool for this diagnosis. The preprocessing stages are the key for any further assessment, since these images exhibit several defects, including non uniform illumination, sampling noise, uneven contrast due to pigmentation loss during sampling, and many others. Any feasible diagnosis system should work with images where these defects were compensated. In this work we analyze and test several correction techniques. Non uniform illumination is compensated using morphology and homomorphic filtering; uneven contrast is compensated using morphology and local enhancement. We tested our processing stages using Fuzzy C-Means, and local Hurst (self correlation) coefficient for unsupervised segmentation of the abnormal blood vessels. The results over a standard set of DR images are more than promising.

Segmentation of retinal blood vessels for detection of diabetic retinopathy: A review

Directory of Open Access Journals (Sweden)

Rezty Amalia Aras

2016-05-01

Full Text Available Diabetic detinopathy (DR is effect of diabetes mellitus to the human vision that is the major cause of blindness. Early diagnosis of DR is an important requirement in diabetes treatment. Retinal fundus image is commonly used to observe the diabetic retinopathy symptoms. It can present retinal features such as blood vessel and also capture the pathologies which may lead to DR. Blood vessel is one of retinal features which can show the retina pathologies. It can be extracted from retinal image by image processing with following stages: pre-processing, segmentation, and post-processing. This paper contains a review of public retinal image dataset and several methods from various conducted researches. All discussed methods are applicable to each researcher cases. There is no further analysis to conclude the best method which can be used for general cases. However, we suggest morphological and multiscale method that gives the best accuracy in segmentation.

Optical Coherence Tomography Angiography in Retinal Diseases.

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Chalam, K V; Sambhav, Kumar

2016-01-01

Optical coherence tomography angiography (OCTA) is a new, non-invasive imaging system that generates volumetric data of retinal and choroidal layers. It has the ability to show both structural and blood flow information. Split-spectrum amplitude-decorrelation angiography (SSADA) algorithm (a vital component of OCTA software) helps to decrease the signal to noise ratio of flow detection thus enhancing visualization of retinal vasculature using motion contrast. Published studies describe potential efficacy for OCTA in the evaluation of common ophthalmologic diseases such as diabetic retinopathy, age related macular degeneration (AMD), retinal vascular occlusions and sickle cell disease. OCTA provides a detailed view of the retinal vasculature, which allows accurate delineation of microvascular abnormalities in diabetic eyes and vascular occlusions. It helps quantify vascular compromise depending upon the severity of diabetic retinopathy. OCTA can also elucidate the presence of choroidal neovascularization (CNV) in wet AMD. In this paper, we review the knowledge, available in English language publications regarding OCTA, and compare it with the conventional angiographic standard, fluorescein angiography (FA). Finally, we summarize its potential applications to retinal vascular diseases. Its current limitations include a relatively small field of view, inability to show leakage, and tendency for image artifacts. Further larger studies will define OCTA's utility in clinical settings and establish if the technology may offer a non-invasive option of visualizing the retinal vasculature, enabling us to decrease morbidity through early detection and intervention in retinal diseases.

[Retinal imaging of the macula and optic disc in neurodegenerative diseases].

Science.gov (United States)

Turski, G N; Schmitz-Valckenberg, S; Holz, F G; Finger, R P

2017-02-01

Due to current demographic trends, the prevalence of mild cognitive impairment and dementia is expected to increase considerably. For potential new therapies it is important to identify patients at risk as early as possible. Currently, there is no population-based screening. Therefore, identification of biomarkers that will help screen the population at risk is urgently needed. Thus, a literature review on retinal pathology in neurodegenerative diseases was performed. PubMed was searched for studies published up to August 2016 using the following keywords: "mild cognitive impairment", "dementia", "eye", "ocular biomarkers", "OCT" and "OCT angiography". Relevant publications were selected and summarized qualitatively. Multiple studies using noninvasive in vivo optical coherence tomography (OCT) imaging showed nonspecific retinal pathological changes in patients with neurodegenerative diseases such as mild cognitive impairment, Alzheimer's and Parkinson's disease. Pathological changes in macular volume, optic nerve fiber layer thickness and the ganglion cell complex were observed. However, based on available evidence, no ocular biomarkers for neurodegeneration which could be integrated in routine clinical diagnostics have been identified. The potential use of OCT in the early diagnostic workup and monitoring of progression of neurodegenerative diseases needs to be further explored in longitudinal studies with large cohorts.

Optical Coherence Tomography Angiography of Retinal Cavernous Hemangioma.

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Pierro, Luisa; Marchese, Alessandro; Gagliardi, Marco; Bandello, Francesco

2017-08-01

Retinal cavernous hemangioma is a rare, benign, retinal tumor characterized by angiomatous proliferation of vessels within the inner retina or the optic disc.1 Here we report a case of retinal cavernous hemangioma on the margin of the optic disc in the right eye of a 61-year-old asymptomatic female. The lesion was studied with multimodal imaging which included structural optical coherence tomography, fluorescein angiography, blue fundus auto-fluorescence, optical coherence tomography angiography (OCTA) (DRI OCT Triton; Topcon, Tokyo, Japan) and visual field examination. Blood circulation inside retinal cavernous hemangioma lesion is typically low-stagnant.2 However, OCTA demonstrated blood flow inside the lesion, illustrating its vascular circulation.3 Visual field was within the normal limits, except from a slight enlargement of the blind spot. [Ophthalmic Surg Lasers Imaging Retina. 2017;48:684-685.]. Copyright 2017, SLACK Incorporated.

Detector response restoration in image reconstruction of high resolution positron emission tomography

International Nuclear Information System (INIS)

Liang, Z.

1994-01-01

A mathematical method was studied to model the detector response of high spatial-resolution positron emission tomography systems consisting of close-packed small crystals, and to restore the resolution deteriorated due to crystal penetration and/or nonuniform sampling across the field-of-view (FOV). The simulated detector system had 600 bismuth germanate crystals of 3.14 mm width and 30 mm length packed on a single ring of 60 cm diameter. The space between crystal was filled up with lead. Each crystal was in coincidence with 200 opposite crystals so that the FOV had a radius of 30 cm. The detector response was modeled based on the attenuating properties of the crystals and the septa, as well as the geometry of the detector system. The modeled detector-response function was used to restore the projections from the sinogram of the ring-detector system. The restored projections had a uniform sampling of 1.57 mm across the FOV. The crystal penetration and/or the nonuniform sampling were compensated in the projections. A penalized maximum-likelihood algorithm was employed to accomplish the restoration. The restored projections were then filtered and backprojected to reconstruct the image. A chest phantom with a few small circular ''cold'' objects located at the center and near the periphery of FOV was computer generated and used to test the restoration. The reconstructed images from the restored projections demonstrated resolution improvement off the FOV center, while preserving the resolution near the center

Neural network based multiscale image restoration approach

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de Castro, Ana Paula A.; da Silva, José D. S.

2007-02-01

This paper describes a neural network based multiscale image restoration approach. Multilayer perceptrons are trained with artificial images of degraded gray level circles, in an attempt to make the neural network learn inherent space relations of the degraded pixels. The present approach simulates the degradation by a low pass Gaussian filter blurring operation and the addition of noise to the pixels at pre-established rates. The training process considers the degraded image as input and the non-degraded image as output for the supervised learning process. The neural network thus performs an inverse operation by recovering a quasi non-degraded image in terms of least squared. The main difference of the approach to existing ones relies on the fact that the space relations are taken from different scales, thus providing relational space data to the neural network. The approach is an attempt to come up with a simple method that leads to an optimum solution to the problem. Considering different window sizes around a pixel simulates the multiscale operation. In the generalization phase the neural network is exposed to indoor, outdoor, and satellite degraded images following the same steps use for the artificial circle image.

Time-resolved PHERMEX image restorations constrained with an additional multiply-exposed image

International Nuclear Information System (INIS)

Kruger, R.P.; Breedlove, J.R. Jr.; Trussell, H.J.

1978-06-01

There are a number of possible industrial and scientific applications of nanosecond cineradiographs. Although the technology exists to produce closely spaced pulses of x rays for this application, the quality of the time-resolved radiographs is severely limited. The limitations arise from the necessity of using a fluorescent screen to convert the transmitted x rays to light and then using electro-optical imaging systems to gate and to record the images with conventional high-speed cameras. It has been proposed that, in addition to the time-resolved images, a conventional multiply exposed radiograph be obtained. This report uses both PHERMEX and conventional photographic simulations to demonstrate that the additional information supplied by the multiply exposed radiograph can be used to improve the quality of digital image restorations of the time-resolved pictures over what could be achieved with the degraded images alone

Imaging of Dual Ophthalmic Arteries: Identification of the Central Retinal Artery

Directory of Open Access Journals (Sweden)

Louise Louw

2014-01-01

Full Text Available Identification of the origin of the central retinal artery (CRA is imperative in tailoring angiographic studies to resolve a given clinical problem. A case with dual ophthalmic arteries (OAs, characterized by different origins and distinct branching patterns, is documented for training purposes. Pre-clinical diagnosis of a 9-year-old child who presented with a sharp wire in the left-side eyeball was primarily corneal laceration. For imaging, a selected six-vessel angiographic study with the transfemoral approach was performed. Embolization was not required and the wire could be successfully removed. Right-side OA anatomy was normal, while left-side dual OAs with external carotid artery (ECA and internal carotid artery (ICA origins were seen. The case presented with a left-side meningo-ophthalmic artery (M-OA anomaly via the ECA, marked by a middle meningeal artery (MMA (origin: Maxillary artery; course: Through foramen spinosum with normal branches (i.e. anterior and posterior branches, and an OA variant (course: Through superior orbital fissure with a distinct orbital branching pattern. A smaller OA (origin: ICA; course: Through optic foramen with a distinct ocular branching pattern presented with the central retinal artery (CRA. The presence of the dual OAs and the M-OA anomaly can be explained by disturbed evolutionary changes of the primitive OA and stapedial artery during development. The surgical interventionist must be aware of dual OAs and M-OA anomalies with branching pattern variations on retinal supply, because of dangerous extracranial-intracranial anastomotic connections. It is of clinical significance that the origin of the CRA from the ICA or ECA must be determined to avoid complications to the vision.

Autofluorescence Imaging and Spectral-Domain Optical Coherence Tomography in Incomplete Congenital Stationary Night Blindness and Comparison with Retinitis Pigmentosa

Science.gov (United States)

CHEN, ROYCE W. S.; GREENBERG, JONATHAN P.; LAZOW, MARGOT A.; RAMACHANDRAN, RITHU; LIMA, LUIZ H.; HWANG, JOHN C.; SCHUBERT, CARL; BRAUNSTEIN, ALEXANDRA; ALLIKMETS, RANDO; TSANG, STEPHEN H.

2015-01-01

PURPOSE To test the hypothesis that the evaluation of retinal structure can have diagnostic value in differentiating between incomplete congenital stationary night blindness (CSNB2) and retinitis pigmentosa (RP). To compare retinal thickness differences between patients with CSNB2 and myopic controls. DESIGN Prospective cross-sectional study. METHODS Ten eyes of 5 patients diagnosed with CSNB2 (4 X-linked recessive, 1 autosomal recessive) and 6 eyes of 3 patients with RP (2 autosomal dominant, 1 autosomal recessive) were evaluated with spectral-domain optical coherence tomography (SD OCT) and fundus autofluorescence (FAF). Diagnoses of CSNB2 and RP were confirmed by full-field electroretinography (ERG). Manual segmentation of retinal layers, aided by a computer program, was performed by 2 professional segmenters on SD OCT images of all CSNB2 patients and 4 age-similar, normal myopic controls. Seven patients were screened for mutations with congenital stationary night blindness and RP genotyping arrays. RESULTS Patients with CSNB2 had specific findings on SD OCT and FAF that were distinct from those found in RP. CSNB2 patients showed qualitatively normal SD OCT results with preserved photoreceptor inner segment/outer segment junction, whereas this junction was lost in RP patients. In addition, CSNB2 patients had normal FAF images, whereas patients with RP demonstrated a ring of increased autofluorescence around the macula. On SD OCT segmentation, the inner and outer retinal layers of both X-linked recessive and autosomal recessive CSNB2 patients were thinner compared with those of normal myopic controls, with means generally outside of normal 95% confidence intervals. The only layers that demonstrated similar thickness between CSNB2 patients and the controls were the retinal nerve fiber layer and, temporal to the fovea, the combined outer segment layer and retinal pigment epithelium. A proband and his 2 affected brothers from a family segregating X-linked recessive

Use of the geometric mean of opposing planar projections in pre-reconstruction restoration of SPECT images

International Nuclear Information System (INIS)

Boulfelfel, D.; Rangayyan, R.M.; Hahn, L.J.; Kloiber, R.

1992-01-01

This paper presents a restoration scheme for single photon emission computed tomography (SPECT) images that performs restoration before reconstruction (pre-reconstruction restoration) from planar (projection) images. In this scheme, the pixel-by-pixel geometric mean of each pair of opposing (conjugate) planar projections is computed prior to the reconstruction process. The averaging process is shown to help in making the degradation phenomenon less dependent on the distance of each point of the object from the camera. The restoration filters investigated are the Wiener and power spectrum equalization filters. (author)

Pharmacologic Activation of Wnt Signaling by Lithium Normalizes Retinal Vasculature in a Murine Model of Familial Exudative Vitreoretinopathy.

Science.gov (United States)

Wang, Zhongxiao; Liu, Chi-Hsiu; Sun, Ye; Gong, Yan; Favazza, Tara L; Morss, Peyton C; Saba, Nicholas J; Fredrick, Thomas W; He, Xi; Akula, James D; Chen, Jing

2016-10-01

Familial exudative vitreoretinopathy (FEVR) is characterized by delayed retinal vascular development, which promotes hypoxia-induced pathologic vessels. In severe cases FEVR may lead to retinal detachment and visual impairment. Genetic studies linked FEVR with mutations in Wnt signaling ligand or receptors, including low-density lipoprotein receptor-related protein 5 (LRP5) gene. Here, we investigated ocular pathologies in a Lrp5 knockout (Lrp5(-/-)) mouse model of FEVR and explored whether treatment with a pharmacologic Wnt activator lithium could bypass the genetic defects, thereby protecting against eye pathologies. Lrp5(-/-) mice displayed significantly delayed retinal vascular development, absence of deep layer retinal vessels, leading to increased levels of vascular endothelial growth factor and subsequent pathologic glomeruloid vessels, as well as decreased inner retinal visual function. Lithium treatment in Lrp5(-/-) mice significantly restored the delayed development of retinal vasculature and the intralaminar capillary networks, suppressed formation of pathologic glomeruloid structures, and promoted hyaloid vessel regression. Moreover, lithium treatment partially rescued inner-retinal visual function and increased retinal thickness. These protective effects of lithium were largely mediated through restoration of canonical Wnt signaling in Lrp5(-/-) retina. Lithium treatment also substantially increased vascular tubular formation in LRP5-deficient endothelial cells. These findings suggest that pharmacologic activation of Wnt signaling may help treat ocular pathologies in FEVR and potentially other defective Wnt signaling-related diseases. Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Molecular imaging reveals elevated VEGFR-2 expression in retinal capillaries in diabetes: a novel biomarker for early diagnosis

OpenAIRE

Sun, Dawei; Nakao, Shintaro; Xie, Fang; Zandi, Souska; Bagheri, Abouzar; Kanavi, Mozhgan Rezaei; Samiei, Shahram; Soheili, Zahra-Soheila; Frimmel, Sonja; Zhang, Zhongyu; Ablonczy, Zsolt; Ahmadieh, Hamid; Hafezi-Moghadam, Ali

2014-01-01

Diabetic retinopathy (DR) is a microvascular complication of diabetes and a leading cause of vision loss. Biomarkers and methods for early diagnosis of DR are urgently needed. Using a new molecular imaging approach, we show up to 94% higher accumulation of custom designed imaging probes against vascular endothelial growth factor receptor 2 (VEGFR-2) in retinal and choroidal vessels of diabetic animals (P

Investigation of retinal morphology alterations using spectral domain optical coherence tomography in a mouse model of retinal branch and central retinal vein occlusion.

Directory of Open Access Journals (Sweden)

Andreas Ebneter

Full Text Available Retinal vein occlusion is a leading cause of visual impairment. Experimental models of this condition based on laser photocoagulation of retinal veins have been described and extensively exploited in mammals and larger rodents such as the rat. However, few reports exist on the use of this paradigm in the mouse. The objective of this study was to investigate a model of branch and central retinal vein occlusion in the mouse and characterize in vivo longitudinal retinal morphology alterations using spectral domain optical coherence tomography. Retinal veins were experimentally occluded using laser photocoagulation after intravenous application of Rose Bengal, a photo-activator dye enhancing thrombus formation. Depending on the number of veins occluded, variable amounts of capillary dropout were seen on fluorescein angiography. Vascular endothelial growth factor levels were markedly elevated early and peaked at day one. Retinal thickness measurements with spectral domain optical coherence tomography showed significant swelling (p<0.001 compared to baseline, followed by gradual thinning plateauing two weeks after the experimental intervention (p<0.001. Histological findings at day seven correlated with spectral domain optical coherence tomography imaging. The inner layers were predominantly affected by degeneration with the outer nuclear layer and the photoreceptor outer segments largely preserved. The application of this retinal vein occlusion model in the mouse carries several advantages over its use in other larger species, such as access to a vast range of genetically modified animals. Retinal changes after experimental retinal vein occlusion in this mouse model can be non-invasively quantified by spectral domain optical coherence tomography, and may be used to monitor effects of potential therapeutic interventions.

Application of morphological bit planes in retinal blood vessel extraction.

Science.gov (United States)

Fraz, M M; Basit, A; Barman, S A

2013-04-01

The appearance of the retinal blood vessels is an important diagnostic indicator of various clinical disorders of the eye and the body. Retinal blood vessels have been shown to provide evidence in terms of change in diameter, branching angles, or tortuosity, as a result of ophthalmic disease. This paper reports the development for an automated method for segmentation of blood vessels in retinal images. A unique combination of methods for retinal blood vessel skeleton detection and multidirectional morphological bit plane slicing is presented to extract the blood vessels from the color retinal images. The skeleton of main vessels is extracted by the application of directional differential operators and then evaluation of combination of derivative signs and average derivative values. Mathematical morphology has been materialized as a proficient technique for quantifying the retinal vasculature in ocular fundus images. A multidirectional top-hat operator with rotating structuring elements is used to emphasize the vessels in a particular direction, and information is extracted using bit plane slicing. An iterative region growing method is applied to integrate the main skeleton and the images resulting from bit plane slicing of vessel direction-dependent morphological filters. The approach is tested on two publicly available databases DRIVE and STARE. Average accuracy achieved by the proposed method is 0.9423 for both the databases with significant values of sensitivity and specificity also; the algorithm outperforms the second human observer in terms of precision of segmented vessel tree.

Modern technologies for retinal scanning and imaging: an introduction for the biomedical engineer

Science.gov (United States)

2014-01-01

This review article is meant to help biomedical engineers and nonphysical scientists better understand the principles of, and the main trends in modern scanning and imaging modalities used in ophthalmology. It is intended to ease the communication between physicists, medical doctors and engineers, and hopefully encourage “classical” biomedical engineers to generate new ideas and to initiate projects in an area which has traditionally been dominated by optical physics. Most of the methods involved are applicable to other areas of biomedical optics and optoelectronics, such as microscopic imaging, spectroscopy, spectral imaging, opto-acoustic tomography, fluorescence imaging etc., all of which are with potential biomedical application. Although all described methods are novel and important, the emphasis of this review has been placed on three technologies introduced in the 1990’s and still undergoing vigorous development: Confocal Scanning Laser Ophthalmoscopy, Optical Coherence Tomography, and polarization-sensitive retinal scanning. PMID:24779618

Integral equation models for image restoration: high accuracy methods and fast algorithms

International Nuclear Information System (INIS)

Lu, Yao; Shen, Lixin; Xu, Yuesheng

2010-01-01

Discrete models are consistently used as practical models for image restoration. They are piecewise constant approximations of true physical (continuous) models, and hence, inevitably impose bottleneck model errors. We propose to work directly with continuous models for image restoration aiming at suppressing the model errors caused by the discrete models. A systematic study is conducted in this paper for the continuous out-of-focus image models which can be formulated as an integral equation of the first kind. The resulting integral equation is regularized by the Lavrentiev method and the Tikhonov method. We develop fast multiscale algorithms having high accuracy to solve the regularized integral equations of the second kind. Numerical experiments show that the methods based on the continuous model perform much better than those based on discrete models, in terms of PSNR values and visual quality of the reconstructed images

A general framework for regularized, similarity-based image restoration.

Science.gov (United States)

Kheradmand, Amin; Milanfar, Peyman

2014-12-01

Any image can be represented as a function defined on a weighted graph, in which the underlying structure of the image is encoded in kernel similarity and associated Laplacian matrices. In this paper, we develop an iterative graph-based framework for image restoration based on a new definition of the normalized graph Laplacian. We propose a cost function, which consists of a new data fidelity term and regularization term derived from the specific definition of the normalized graph Laplacian. The normalizing coefficients used in the definition of the Laplacian and associated regularization term are obtained using fast symmetry preserving matrix balancing. This results in some desired spectral properties for the normalized Laplacian such as being symmetric, positive semidefinite, and returning zero vector when applied to a constant image. Our algorithm comprises of outer and inner iterations, where in each outer iteration, the similarity weights are recomputed using the previous estimate and the updated objective function is minimized using inner conjugate gradient iterations. This procedure improves the performance of the algorithm for image deblurring, where we do not have access to a good initial estimate of the underlying image. In addition, the specific form of the cost function allows us to render the spectral analysis for the solutions of the corresponding linear equations. In addition, the proposed approach is general in the sense that we have shown its effectiveness for different restoration problems, including deblurring, denoising, and sharpening. Experimental results verify the effectiveness of the proposed algorithm on both synthetic and real examples.

Cytomegalovirus retinitis and HIV: Case reviews from KwaZulu ...

African Journals Online (AJOL)

untreated, CMV retinitis can progress to retinal detachment with ... 1 Centre for the AIDS Programme of Research in South Africa (CAPRISA), Doris .... [18] Ocular TB .... patients for publication of these case reviews and accompanying images.

Image restorations constrained by a multiply exposed picture

International Nuclear Information System (INIS)

Breedlove, J.R. Jr.; Kruger, R.P.; Trussell, H.J.; Hunt, B.R.

1977-01-01

There are a number of possible industrial and scientific applications of nanosecond cineradiographs. While the technology exists to produce closely spaced pulses of x rays for this application, the quality of the time-resolved radiographs is severely limited. The limitations arise from the necessity of using a fluorescent screen to convert the transmitted x rays to light and then using electro-optical imaging systems to gate and to record the images with conventional high-speed cameras. It has been proposed that in addition to the time-resolved images, a conventional multiply-exposed radiograph be obtained. Simulations are used to demonstrate that the additional information supplied by the multiply-exposed radiograph can be used to improve the quality of digital image restorations of the time-resolved pictures over what could be achieved with the degraded images alone. Because of the need for image registration and rubber sheet transformations, this problem is one which can best be solved on a digital, as opposed to an optical, computer

Automated retinal fovea type distinction in spectral-domain optical coherence tomography of retinal vein occlusion

Science.gov (United States)

Wu, Jing; Waldstein, Sebastian M.; Gerendas, Bianca S.; Langs, Georg; Simader, Christian; Schmidt-Erfurth, Ursula

2015-03-01

Spectral-domain Optical Coherence Tomography (SD-OCT) is a non-invasive modality for acquiring high- resolution, three-dimensional (3D) cross-sectional volumetric images of the retina and the subretinal layers. SD-OCT also allows the detailed imaging of retinal pathology, aiding clinicians in the diagnosis of sight degrading diseases such as age-related macular degeneration (AMD), glaucoma and retinal vein occlusion (RVO). Disease diagnosis, assessment, and treatment will require a patient to undergo multiple OCT scans, possibly using multiple scanners, to accurately and precisely gauge disease activity, progression and treatment success. However, cross-vendor imaging and patient movement may result in poor scan spatial correlation potentially leading to incorrect diagnosis or treatment analysis. The retinal fovea is the location of the highest visual acuity and is present in all patients, thus it is critical to vision and highly suitable for use as a primary landmark for cross-vendor/cross-patient registration for precise comparison of disease states. However, the location of the fovea in diseased eyes is extremely challenging to locate due to varying appearance and the presence of retinal layer destroying pathology. Thus categorising and detecting the fovea type is an important prior stage to automatically computing the fovea position. Presented here is an automated cross-vendor method for fovea distinction in 3D SD-OCT scans of patients suffering from RVO, categorising scans into three distinct types. OCT scans are preprocessed by motion correction and noise filing followed by segmentation using a kernel graph-cut approach. A statistically derived mask is applied to the resulting scan creating an ROI around the probable fovea location from which the uppermost retinal surface is delineated. For a normal appearance retina, minimisation to zero thickness is computed using the top two retinal surfaces. 3D local minima detection and layer thickness analysis are used

Diffusion tensor imaging of the optic tracts in multiple sclerosis: association with retinal thinning and visual disability.

Science.gov (United States)

Dasenbrock, Hormuzdiyar H; Smith, Seth A; Ozturk, Arzu; Farrell, Sheena K; Calabresi, Peter A; Reich, Daniel S

2011-04-01

Visual disability is common in multiple sclerosis, but its relationship to abnormalities of the optic tracts remains unknown. Because they are only rarely affected by lesions, the optic tracts may represent a good model for assessing the imaging properties of normal-appearing white matter in multiple sclerosis. Whole-brain diffusion tensor imaging was performed on 34 individuals with multiple sclerosis and 26 healthy volunteers. The optic tracts were reconstructed by tractography, and tract-specific diffusion indices were quantified. In the multiple-sclerosis group, peripapillary retinal nerve-fiber-layer thickness and total macular volume were measured by optical coherence tomography, and visual acuity at 100%, 2.5%, and 1.25% contrast was examined. After adjusting for age and sex, optic-tract mean and perpendicular diffusivity were higher (P=.002) in multiple sclerosis. Lower optic-tract fractional anisotropy was correlated with retinal nerve-fiber-layer thinning (r=.51, P=.003) and total-macular-volume reduction (r=.59, P=.002). However, optic-tract diffusion indices were not specifically correlated with visual acuity or with their counterparts in the optic radiation. Optic-tract diffusion abnormalities are associated with retinal damage, suggesting that both may be related to optic-nerve injury, but do not appear to contribute strongly to visual disability in multiple sclerosis. Copyright © 2010 by the American Society of Neuroimaging.

Thickness related textural properties of retinal nerve fiber layer in color fundus images.

Science.gov (United States)

Odstrcilik, Jan; Kolar, Radim; Tornow, Ralf-Peter; Jan, Jiri; Budai, Attila; Mayer, Markus; Vodakova, Martina; Laemmer, Robert; Lamos, Martin; Kuna, Zdenek; Gazarek, Jiri; Kubena, Tomas; Cernosek, Pavel; Ronzhina, Marina

2014-09-01

Images of ocular fundus are routinely utilized in ophthalmology. Since an examination using fundus camera is relatively fast and cheap procedure, it can be used as a proper diagnostic tool for screening of retinal diseases such as the glaucoma. One of the glaucoma symptoms is progressive atrophy of the retinal nerve fiber layer (RNFL) resulting in variations of the RNFL thickness. Here, we introduce a novel approach to capture these variations using computer-aided analysis of the RNFL textural appearance in standard and easily available color fundus images. The proposed method uses the features based on Gaussian Markov random fields and local binary patterns, together with various regression models for prediction of the RNFL thickness. The approach allows description of the changes in RNFL texture, directly reflecting variations in the RNFL thickness. Evaluation of the method is carried out on 16 normal ("healthy") and 8 glaucomatous eyes. We achieved significant correlation (normals: ρ=0.72±0.14; p≪0.05, glaucomatous: ρ=0.58±0.10; p≪0.05) between values of the model predicted output and the RNFL thickness measured by optical coherence tomography, which is currently regarded as a standard glaucoma assessment device. The evaluation thus revealed good applicability of the proposed approach to measure possible RNFL thinning. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Challenges and advantages in wide-field optical coherence tomography angiography imaging of the human retinal and choroidal vasculature at 1.7-MHz A-scan rate

Science.gov (United States)

Poddar, Raju; Migacz, Justin V.; Schwartz, Daniel M.; Werner, John S.; Gorczynska, Iwona

2017-10-01

We present noninvasive, three-dimensional, depth-resolved imaging of human retinal and choroidal blood circulation with a swept-source optical coherence tomography (OCT) system at 1065-nm center wavelength. Motion contrast OCT imaging was performed with the phase-variance OCT angiography method. A Fourier-domain mode-locked light source was used to enable an imaging rate of 1.7 MHz. We experimentally demonstrate the challenges and advantages of wide-field OCT angiography (OCTA). In the discussion, we consider acquisition time, scanning area, scanning density, and their influence on visualization of selected features of the retinal and choroidal vascular networks. The OCTA imaging was performed with a field of view of 16 deg (5 mm×5 mm) and 30 deg (9 mm×9 mm). Data were presented in en face projections generated from single volumes and in en face projection mosaics generated from up to 4 datasets. OCTA imaging at 1.7 MHz A-scan rate was compared with results obtained from a commercial OCTA instrument and with conventional ophthalmic diagnostic methods: fundus photography, fluorescein, and indocyanine green angiography. Comparison of images obtained from all methods is demonstrated using the same eye of a healthy volunteer. For example, imaging of retinal pathology is presented in three cases of advanced age-related macular degeneration.

Radiopacity of restorative composites by conventional radiography and digital images with different resolutions

Energy Technology Data Exchange (ETDEWEB)

Dantas, Raquel Venancio; Samento, Hugo Ramalho [Graduate Program in Dentistry, Federal University of Pelotas, Pelotas (Brazil); Duarte, Rosangela Marques; Raso, Sonia Saeger Meireles Monte; De Andrade Ana Karina Maciel; Anjos-Pontual Maria Luiza Dos [Dept. of Operative Dentistry, Federal University of Paraiba, Pelotas (Brazil)

2013-09-15

This study was performed to evaluate and compare the radiopacity of dentin, enamel, and 8 restorative composites on conventional radiograph and digital images with different resolutions. Specimens were fabricated from 8 materials and human molars were longitudinally sectioned 1.0 mm thick to include both enamel and dentin. The specimens and tooth sections were imaged by conventional radiograph using 4 sized intraoral film and digital images were taken in high speed and high resolution modes using a phosphor storage plate. Densitometric evaluation of the enamel, dentin, restorative materials, a lead sheet, and an aluminum step wedge was performed on the radiographic images. For the evaluation, the Al equivalent (mm) for each material was calculated. The data were analyzed using one-way ANOVA and Tukey's test (p<0.05), considering the material factor and then the radiographic method factor, individually. The high speed mode allowed the highest radiopacity, while the high resolution mode generated the lowest values. Furthermore, the high resolution mode was the most efficient method for radiographic differentiation between restorative composites and dentin. The conventional radiograph was the most effective in enabling differentiation between enamel and composites. The high speed mode was the least effective in enabling radiographic differentiation between the dental tissues and restorative composites. The high speed mode of digital imaging was not effective for differentiation between enamel and composites. This made it less effective than the high resolution mode and conventional radiographs. All of the composites evaluated showed radiopacity values that fit the ISO 4049 recommendations.

A new method by steering kernel-based Richardson–Lucy algorithm for neutron imaging restoration

International Nuclear Information System (INIS)

Qiao, Shuang; Wang, Qiao; Sun, Jia-ning; Huang, Ji-peng

2014-01-01

Motivated by industrial applications, neutron radiography has become a powerful tool for non-destructive investigation techniques. However, resulted from a combined effect of neutron flux, collimated beam, limited spatial resolution of detector and scattering, etc., the images made with neutrons are degraded severely by blur and noise. For dealing with it, by integrating steering kernel regression into Richardson–Lucy approach, we present a novel restoration method in this paper, which is capable of suppressing noise while restoring details of the blurred imaging result efficiently. Experimental results show that compared with the other methods, the proposed method can improve the restoration quality both visually and quantitatively

Application of digital techniques to the restoration of radiographic images

International Nuclear Information System (INIS)

Burch, S.F.

1980-09-01

The methods of constrained least squares and maximum entropy have been used to restore digital X and γ-ray radiographs. Both methods require the blurring of the image to be a linear, spatially invariant process. Although the blurring processes in radiography can be complex, situations have been identified where these simplifying assumptions are valid. Algorithms for deriving the point-spread function of each image are discussed. These include a pinhole method for X-ray radiographs, and reconstruction from edge profiles for γ-ray radiographs. The results from the restoration of geometrically blurred radiographs of sparking plugs are given. Maximum entropy gives results superior to those obtained by constrained least squares. The resolution is improved by a factor of about three when maximum entropy is used, and by a factor of about two for constrained least squares. (author)

Influence of transverse mode on retinal spot size and retinal injury effect: A theoretical analysis on 532-nm laser

Directory of Open Access Journals (Sweden)

Jia-Rui Wang

2014-05-01

Full Text Available The fundamental transverse mode (TEM00 is preferable for experimental and theoretical study on the laser-induced retinal injury effect, for it can produce the minimal retinal image and establish the most strict laser safety standards. But actually lasers with higher order mode were frequently used in both earlier and recent studies. Generally higher order mode leads to larger retinal spot size and so higher damage threshold, but there are few quantitative analyses on this problem. In this paper, a four-surface schematic eye model is established for human and macaque. The propagation of 532-nm laser in schematic eye is analyzed by the ABCD law of Gaussian optics. It is shown that retinal spot size increases with laser transverse mode order. For relative lower mode order, the retinal spot diameter will not exceed the minimum laser-induced retinal lesion (25 ~ 30 μm in diameter, and so has little effect on retinal damage threshold. While for higher order mode, the larger retinal spot requires more energy to induce injury and so the damage threshold increases. When beam divergence is lowered, the retinal spot size decreases correspondingly, so the effect of mode order can be compensated. The retinal spot size of macaque is slightly smaller than that of human and the ratio between them is independent of mode order. We conclude that the laser mode order has significant influence on retinal spot size but limited influence on the retinal injury effect.

Comparison of low-cost handheld retinal camera and traditional table top retinal camera in the detection of retinal features indicating a risk of cardiovascular disease

Science.gov (United States)

Joshi, V.; Wigdahl, J.; Nemeth, S.; Zamora, G.; Ebrahim, E.; Soliz, P.

2018-02-01

Retinal abnormalities associated with hypertensive retinopathy are useful in assessing the risk of cardiovascular disease, heart failure, and stroke. Assessing these risks as part of primary care can lead to a decrease in the incidence of cardiovascular disease-related deaths. Primary care is a resource limited setting where low cost retinal cameras may bring needed help without compromising care. We compared a low-cost handheld retinal camera to a traditional table top retinal camera on their optical characteristics and performance to detect hypertensive retinopathy. A retrospective dataset of N=40 subjects (28 with hypertensive retinopathy, 12 controls) was used from a clinical study conducted at a primary care clinic in Texas. Non-mydriatic retinal fundus images were acquired using a Pictor Plus hand held camera (Volk Optical Inc.) and a Canon CR1-Mark II tabletop camera (Canon USA) during the same encounter. The images from each camera were graded by a licensed optometrist according to the universally accepted Keith-Wagener-Barker Hypertensive Retinopathy Classification System, three weeks apart to minimize memory bias. The sensitivity of the hand-held camera to detect any level of hypertensive retinopathy was 86% compared to the Canon. Insufficient photographer's skills produced 70% of the false negative cases. The other 30% were due to the handheld camera's insufficient spatial resolution to resolve the vascular changes such as minor A/V nicking and copper wiring, but these were associated with non-referable disease. Physician evaluation of the performance of the handheld camera indicates it is sufficient to provide high risk patients with adequate follow up and management.

Restoring proximal caries lesions conservatively with tunnel restorations.

Science.gov (United States)

Chu, Chun-Hung; Mei, May L; Cheung, Chloe; Nalliah, Romesh P

2013-07-30

The tunnel restoration has been suggested as a conservative alternative to the conventional box preparation for treating proximal caries. The main advantage of tunnel restoration over the conventional box or slot preparation includes being more conservative and increasing tooth integrity and strength by preserving the marginal ridge. However, tunnel restoration is technique-sensitive and can be particularly challenging for inexperienced restorative dentists. Recent advances in technology, such as the contemporary design of dental handpieces with advanced light-emitting diode (LED) and handheld comfort, offer operative dentists better vision, illumination, and maneuverability. The use of magnifying loupes also enhances the visibility of the preparation. The advent of digital radiographic imaging has improved dental imaging and reduced radiation. The new generation of restorative materials has improved mechanical properties. Tunnel restoration can be an option to restore proximal caries if the dentist performs proper case selection and pays attention to the details of the restorative procedures. This paper describes the clinical technique of tunnel restoration and reviews the studies of tunnel restorations.

Retinal detachment and retinal holes in retinitis pigmentosa sine pigmento.

Science.gov (United States)

Csaky, K; Olk, R J; Mahl, C F; Bloom, S M

1991-01-01

Retinal detachment and retinal holes in two family members with retinitis pigmentosa sine pigmento are reported. We believe these are the first such cases reported in the literature. We describe the presenting symptoms and management, including cryotherapy, scleral buckling procedure, and sulfur hexafluoride injection (SF6), resulting in stable visual acuity in one case and retinal reattachment and improved visual acuity in the other case.

Platform image processing to study the structural properties of retinal vessel

Directory of Open Access Journals (Sweden)

Miguel Ángel MERCHÁN

2013-05-01

Full Text Available This paper presents a technological platform specialized in assessing retinal vessel caliber and describing the relationship of the results obtained to cardiovascular risk. Retinal circulation is an area of active research by numerous groups, and there is general experimental agreement on the analysis of the patterns of the retinal blood vessels in the normal human retina. The development of automated tools designed to improve performance and decrease interobserver variability, therefore, appears necessary. 

Avascular Retinal Findings in a Child With Achondroplasia.

Science.gov (United States)

Hua, Hong-Uyen T; Tran, Kimberly D; Medina, Carlos A; Fallas, Brenda; Negron, Cathy; Berrocal, Audina M

2017-03-01

The authors present clinical and angiographic findings in a 12-year-old girl with achondroplasia who presented with bilateral retinal peripheral nonperfusion and unilateral rhegmatogenous retinal detachment, which has not been previously described in achondroplasia. This report contributes incremental knowledge regarding aberrant retinal vascular phenomena observed in pediatric disease states and implicates the possible role of mutations in the FGFR3 gene in peripheral vascular abnormalities. [Ophthalmic Surg Lasers Imaging Retina. 2017;48:272-274.]. Copyright 2017, SLACK Incorporated.

Retinal oxygen saturation before and after glaucoma surgery.

Science.gov (United States)

Nitta, Eri; Hirooka, Kazuyuki; Shimazaki, Takeru; Sato, Shino; Ukegawa, Kaori; Nakano, Yuki; Tsujikawa, Akitaka

2017-08-01

This study compared retinal vessel oxygen saturation before and after glaucoma surgery. Retinal oxygen saturation in glaucoma patients was measured using a non-invasive spectrophotometric retinal oximeter. Adequate image quality was found in 49 of the 108 consecutive glaucoma patients recruited, with 30 undergoing trabeculectomy, 11 EX-PRESS and eight trabeculotomy. Retinal oxygen saturation measurements in the retinal arterioles and venules were performed at 1 day prior to and at approximately 10 days after surgery. Statistical analysis was performed using a Student's t-test. After glaucoma surgery, intraocular pressure (IOP) decreased from 19.8 ± 7.7 mmHg to 9.0 ± 5.7 mmHg (p glaucoma surgery had an effect on the retinal venous oxygen saturation. © 2016 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics

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Dongming Li

2017-04-01

Full Text Available An adaptive optics (AO system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.

RESTORATION OF WEAK PHASE-CONTRAST IMAGES RECORDED WITH A HIGH DEGREE OF DEFOCUS: THE"TWIN IMAGE" PROBLEM ASSOCIATED WITH CTF CORRECTION

Energy Technology Data Exchange (ETDEWEB)

Downing, Kenneth H.; Glaeser, Robert M.

2008-03-28

Relatively large values of objective-lens defocus must normally be used to produce detectable levels of image contrast for unstained biological specimens, which are generally weak phase objects. As a result, a subsequent restoration operation must be used to correct for oscillations in the contrast transfer function (CTF) at higher resolution. Currently used methods of CTF-correction assume the ideal case in which Friedel mates in the scattered wave have contributed pairs of Fourier components that overlap with one another in the image plane. This"ideal" situation may be only poorly satisfied, or not satisfied at all, as the particle size gets smaller, the defocus value gets larger, and the resolution gets higher. We have therefore investigated whether currently used methods of CTF correction are also effective in restoring the single-sideband image information that becomes displaced (delocalized) by half (or more) the diameter of a particle of finite size. Computer simulations are used to show that restoration either by"phase flipping" or by multiplying by the CTF recovers only about half of the delocalized information. The other half of the delocalized information goes into a doubly defocused"twin" image of the type produced during optical reconstruction of an in-line hologram. Restoration with a Wiener filter is effective in recovering the delocalized information only when the signal-to-noise ratio (S/N) is orders of magnitude higher than that which exists in low-dose images of biological specimens, in which case the Wiener filter approaches division by the CTF (i.e. the formal inverse). For realistic values of the S/N, however, the"twin image" problem seenwith a Wiener filter is very similar to that seen when either phase flipping or multiplying by the CTF are used for restoration. The results of these simulations suggest that CTF correction is a poor alternative to using a Zernike-type phase plate when imaging biological specimens, in which case the images can

Reading visual braille with a retinal prosthesis.

Science.gov (United States)

Lauritzen, Thomas Z; Harris, Jordan; Mohand-Said, Saddek; Sahel, Jose A; Dorn, Jessy D; McClure, Kelly; Greenberg, Robert J

2012-01-01

Retinal prostheses, which restore partial vision to patients blinded by outer retinal degeneration, are currently in clinical trial. The Argus II retinal prosthesis system was recently awarded CE approval for commercial use in Europe. While retinal prosthesis users have achieved remarkable visual improvement to the point of reading letters and short sentences, the reading process is still fairly cumbersome. This study investigates the possibility of using an epiretinal prosthesis to stimulate visual braille as a sensory substitution for reading written letters and words. The Argus II retinal prosthesis system, used in this study, includes a 10 × 6 electrode array implanted epiretinally, a tiny video camera mounted on a pair of glasses, and a wearable computer that processes the video and determines the stimulation current of each electrode in real time. In the braille reading system, individual letters are created by a subset of dots from a 3 by 2 array of six dots. For the visual braille experiment, a grid of six electrodes was chosen out of the 10 × 6 Argus II array. Groups of these electrodes were then directly stimulated (bypassing the camera) to create visual percepts of individual braille letters. Experiments were performed in a single subject. Single letters were stimulated in an alternative forced choice (AFC) paradigm, and short 2-4-letter words were stimulated (one letter at a time) in an open-choice reading paradigm. The subject correctly identified 89% of single letters, 80% of 2-letter, 60% of 3-letter, and 70% of 4-letter words. This work suggests that text can successfully be stimulated and read as visual braille in retinal prosthesis patients.

Retinal oximetry in patients with ischaemic retinal diseases

DEFF Research Database (Denmark)

Rilvén, Sandra; Torp, Thomas Lee; Grauslund, Jakob

2017-01-01

The retinal oximeter is a new tool for non-invasive measurement of retinal oxygen saturation in humans. Several studies have investigated the associations between retinal oxygen saturation and retinal diseases. In the present systematic review, we examine whether there are associations between...... retinal oxygen saturation and retinal ischaemic diseases. We used PubMed and Embase to search for retinal oxygen saturation and retinal ischaemic diseases. Three separate searches identified a total of 79 publications. After two levels of manual screening, 10 studies were included: six about diabetic...... retinopathy (DR) and four about retinal vein occlusion. No studies about retinal artery occlusion were included. In diabetes, all studies found that increases in retinal venous oxygen saturation (rvSatO2 ) were associated with present as well as increasing levels of DR. Four of six studies also found...

Association of Retinopathy and Retinal Microvascular Abnormalities With Stroke and Cerebrovascular Disease.

Science.gov (United States)

Hughes, Alun D; Falaschetti, Emanuela; Witt, Nicholas; Wijetunge, Sumangali; Thom, Simon A McG; Tillin, Therese; Aldington, Steve J; Chaturvedi, Nish

2016-11-01

Abnormalities of the retinal circulation may be associated with cerebrovascular disease. We investigated associations between retinal microvascular abnormalities and (1) strokes and subclinical cerebral infarcts and (2) cerebral white matter lesions in a UK-based triethnic population-based cohort. A total of 1185 participants (age, 68.8±6.1 years; 77% men) underwent retinal imaging and cerebral magnetic resonance imaging. Cerebral infarcts and white matter hyperintensities were identified on magnetic resonance imaging, retinopathy was graded, and retinal vessels were measured. Higher retinopathy grade (odds ratio [OR], 1.40 [95% confidence interval (95% CI), 1.16-1.70]), narrower arteriolar diameter (OR, 0.98 [95% CI, 0.97-0.99]), fewer symmetrical arteriolar bifurcations (OR, 0.84 [95% CI, 0.75-0.95]), higher arteriolar optimality deviation (OR, 1.16 [95% CI, 1.00-1.34]), and more tortuous venules (OR, 1.20 [95% CI, 1.09-1.32]) were associated with strokes/infarcts and white matter hyperintensities. Associations with quantitative retinal microvascular measures were independent of retinopathy. Abnormalities of the retinal microvasculature are independently associated with stroke, cerebral infarcts, and white matter lesions. © 2016 American Heart Association, Inc.

Comparative Study of Retinal Vessel Segmentation Based on Global Thresholding Techniques

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Temitope Mapayi

2015-01-01

Full Text Available Due to noise from uneven contrast and illumination during acquisition process of retinal fundus images, the use of efficient preprocessing techniques is highly desirable to produce good retinal vessel segmentation results. This paper develops and compares the performance of different vessel segmentation techniques based on global thresholding using phase congruency and contrast limited adaptive histogram equalization (CLAHE for the preprocessing of the retinal images. The results obtained show that the combination of preprocessing technique, global thresholding, and postprocessing techniques must be carefully chosen to achieve a good segmentation performance.

Missed retinal breaks in rhegmatogenous retinal detachment

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Brijesh Takkar

2016-12-01

Full Text Available AIM: To evaluate the causes and associations of missed retinal breaks (MRBs and posterior vitreous detachment (PVD in patients with rhegmatogenous retinal detachment (RRD. METHODS: Case sheets of patients undergoing vitreo retinal surgery for RRD at a tertiary eye care centre were evaluated retrospectively. Out of the 378 records screened, 253 were included for analysis of MRBs and 191 patients were included for analysis of PVD, depending on the inclusion criteria. Features of RRD and retinal breaks noted on examination were compared to the status of MRBs and PVD detected during surgery for possible associations. RESULTS: Overall, 27% patients had MRBs. Retinal holes were commonly missed in patients with lattice degeneration while missed retinal tears were associated with presence of complete PVD. Patients operated for cataract surgery were significantly associated with MRBs (P=0.033 with the odds of missing a retinal break being 1.91 as compared to patients with natural lens. Advanced proliferative vitreo retinopathy (PVR and retinal bullae were the most common reasons for missing a retinal break during examination. PVD was present in 52% of the cases and was wrongly assessed in 16%. Retinal bullae, pseudophakia/aphakia, myopia, and horse shoe retinal tears were strongly associated with presence of PVD. Traumatic RRDs were rarely associated with PVD. CONCLUSION: Pseudophakic patients, and patients with retinal bullae or advanced PVR should be carefully screened for MRBs. Though Weiss ring is a good indicator of PVD, it may still be over diagnosed in some cases. PVD is associated with retinal bullae and pseudophakia, and inversely with traumatic RRD.

Retinal Prosthesis System for Advanced Retinitis Pigmentosa: A Health Technology Assessment Update

Science.gov (United States)

Lee, Christine; Tu, Hong Anh; Wells, David; Holubowich, Corinne

2017-01-01

Background Retinitis pigmentosa is a group of inherited disorders characterized by the degeneration of the photoreceptors in the retina, resulting in progressive vision loss. The Argus II system is designed to restore partial functional vision in patients with profound vision loss from advanced retinitis pigmentosa. At present, it is the only treatment option approved by Health Canada for this patient population. In June 2016, Health Quality Ontario published a health technology assessment of the Argus II retinal prosthesis system for patients with advanced retinitis pigmentosa. Based on that assessment, the Ontario Health Technology Advisory Committee recommended against publicly funding the Argus II system for this population. It also recommended that Health Quality Ontario re-evaluate the evidence in 1 year. The objective of this report was to examine new evidence published since the 2016 health technology assessment. Methods We completed a health technology assessment, which included an evaluation of clinical benefits and harms, value for money, and patient preferences related to the Argus II system. We performed a systematic literature search for studies published since the 2016 Argus II health technology assessment. We developed a Markov decision-analytic model to assess the cost-effectiveness of the Argus II system compared with standard care, and we calculated incremental cost-effectiveness ratios over a 20-year time horizon. We also conducted a five-year budget impact analysis. Finally, we interviewed people with retinitis pigmentosa about their lived experience with vision loss, and with the Argus II system. Results Four publications from one multicentre international study were included in the clinical review. Patients showed significant improvements in visual function and functional outcomes with the Argus II system, and these outcomes were sustained up to a 5-year follow-up (moderate quality of evidence). The safety profile was generally acceptable. In

Low-dose computed tomography image restoration using previous normal-dose scan

International Nuclear Information System (INIS)

Ma, Jianhua; Huang, Jing; Feng, Qianjin; Zhang, Hua; Lu, Hongbing; Liang, Zhengrong; Chen, Wufan

2011-01-01

Purpose: In current computed tomography (CT) examinations, the associated x-ray radiation dose is of a significant concern to patients and operators. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) or kVp parameter (or delivering less x-ray energy to the body) as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and the noise would propagate into the CT image if no adequate noise control is applied during image reconstruction. Since a normal-dose high diagnostic CT image scanned previously may be available in some clinical applications, such as CT perfusion imaging and CT angiography (CTA), this paper presents an innovative way to utilize the normal-dose scan as a priori information to induce signal restoration of the current low-dose CT image series. Methods: Unlike conventional local operations on neighboring image voxels, nonlocal means (NLM) algorithm utilizes the redundancy of information across the whole image. This paper adapts the NLM to utilize the redundancy of information in the previous normal-dose scan and further exploits ways to optimize the nonlocal weights for low-dose image restoration in the NLM framework. The resulting algorithm is called the previous normal-dose scan induced nonlocal means (ndiNLM). Because of the optimized nature of nonlocal weights calculation, the ndiNLM algorithm does not depend heavily on image registration between the current low-dose and the previous normal-dose CT scans. Furthermore, the smoothing parameter involved in the ndiNLM algorithm can be adaptively estimated based on the image noise relationship between the current low-dose and the previous normal-dose scanning protocols. Results: Qualitative and quantitative evaluations were carried out on a physical phantom as well as clinical abdominal and brain perfusion CT scans in terms of accuracy and resolution properties. The gain by the use

Early Detection of Diabetic Retinopathy in Fluorescent Angiography Retinal Images Using Image Processing Methods

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Meysam Tavakoli

2010-12-01

Full Text Available Introduction: Diabetic retinopathy (DR is the single largest cause of sight loss and blindness in the working age population of Western countries; it is the most common cause of blindness in adults between 20 and 60 years of age. Early diagnosis of DR is critical for preventing vision loss so early detection of microaneurysms (MAs as the first signs of DR is important. This paper addresses the automatic detection of MAs in fluorescein angiography fundus images, which plays a key role in computer assisted diagnosis of DR, a serious and frequent eye disease. Material and Methods: The algorithm can be divided into three main steps. The first step or pre-processing was for background normalization and contrast enhancement of the image. The second step aimed at detecting landmarks, i.e., all patterns possibly corresponding to vessels and the optic nerve head, which was achieved using a local radon transform. Then, MAs were extracted, which were used in the final step to automatically classify candidates into real MA and other objects. A database of 120 fluorescein angiography fundus images was used to train and test the algorithm. The algorithm was compared to manually obtained gradings of those images. Results: Sensitivity of diagnosis for DR was 94%, with specificity of 75%, and sensitivity of precise microaneurysm localization was 92%, at an average number of 8 false positives per image. Discussion and Conclusion: Sensitivity and specificity of this algorithm make it one of the best methods in this field. Using local radon transform in this algorithm eliminates the noise sensitivity for microaneurysm detection in retinal image analysis.

Automated segmentation of geographic atrophy of the retinal epithelium via random forests in AREDS color fundus images.

Science.gov (United States)

Feeny, Albert K; Tadarati, Mongkol; Freund, David E; Bressler, Neil M; Burlina, Philippe

2015-10-01

Age-related macular degeneration (AMD), left untreated, is the leading cause of vision loss in people older than 55. Severe central vision loss occurs in the advanced stage of the disease, characterized by either the in growth of choroidal neovascularization (CNV), termed the "wet" form, or by geographic atrophy (GA) of the retinal pigment epithelium (RPE) involving the center of the macula, termed the "dry" form. Tracking the change in GA area over time is important since it allows for the characterization of the effectiveness of GA treatments. Tracking GA evolution can be achieved by physicians performing manual delineation of GA area on retinal fundus images. However, manual GA delineation is time-consuming and subject to inter-and intra-observer variability. We have developed a fully automated GA segmentation algorithm in color fundus images that uses a supervised machine learning approach employing a random forest classifier. This algorithm is developed and tested using a dataset of images from the NIH-sponsored Age Related Eye Disease Study (AREDS). GA segmentation output was compared against a manual delineation by a retina specialist. Using 143 color fundus images from 55 different patient eyes, our algorithm achieved PPV of 0.82±0.19, and NPV of 0:95±0.07. This is the first study, to our knowledge, applying machine learning methods to GA segmentation on color fundus images and using AREDS imagery for testing. These preliminary results show promising evidence that machine learning methods may have utility in automated characterization of GA from color fundus images. Copyright © 2015 Elsevier Ltd. All rights reserved.

CRALBP supports the mammalian retinal visual cycle and cone vision.

Science.gov (United States)

Xue, Yunlu; Shen, Susan Q; Jui, Jonathan; Rupp, Alan C; Byrne, Leah C; Hattar, Samer; Flannery, John G; Corbo, Joseph C; Kefalov, Vladimir J

2015-02-01

Mutations in the cellular retinaldehyde-binding protein (CRALBP, encoded by RLBP1) can lead to severe cone photoreceptor-mediated vision loss in patients. It is not known how CRALBP supports cone function or how altered CRALBP leads to cone dysfunction. Here, we determined that deletion of Rlbp1 in mice impairs the retinal visual cycle. Mice lacking CRALBP exhibited M-opsin mislocalization, M-cone loss, and impaired cone-driven visual behavior and light responses. Additionally, M-cone dark adaptation was largely suppressed in CRALBP-deficient animals. While rearing CRALBP-deficient mice in the dark prevented the deterioration of cone function, it did not rescue cone dark adaptation. Adeno-associated virus-mediated restoration of CRALBP expression specifically in Müller cells, but not retinal pigment epithelial (RPE) cells, rescued the retinal visual cycle and M-cone sensitivity in knockout mice. Our results identify Müller cell CRALBP as a key component of the retinal visual cycle and demonstrate that this pathway is important for maintaining normal cone-driven vision and accelerating cone dark adaptation.

Molecular imaging reveals elevated VEGFR-2 expression in retinal capillaries in diabetes: a novel biomarker for early diagnosis.

Science.gov (United States)

Sun, Dawei; Nakao, Shintaro; Xie, Fang; Zandi, Souska; Bagheri, Abouzar; Kanavi, Mozhgan Rezaei; Samiei, Shahram; Soheili, Zahra-Soheila; Frimmel, Sonja; Zhang, Zhongyu; Ablonczy, Zsolt; Ahmadieh, Hamid; Hafezi-Moghadam, Ali

2014-09-01

Diabetic retinopathy (DR) is a microvascular complication of diabetes and a leading cause of vision loss. Biomarkers and methods for early diagnosis of DR are urgently needed. Using a new molecular imaging approach, we show up to 94% higher accumulation of custom designed imaging probes against vascular endothelial growth factor receptor 2 (VEGFR-2) in retinal and choroidal vessels of diabetic animals (P<0.01), compared to normal controls. More than 80% of the VEGFR-2 in the diabetic retina was in the capillaries, compared to 47% in normal controls (P<0.01). Angiography in rabbit retinas revealed microvascular capillaries to be the location for VEGF-A-induced leakage, as expressed by significantly higher rate of fluorophore spreading with VEGF-A injection when compared to vehicle control (26±2 vs. 3±1 μm/s, P<0.05). Immunohistochemistry showed VEGFR-2 expression in capillaries of diabetic animals but not in normal controls. Macular vessels from diabetic patients (n=7) showed significantly more VEGFR-2 compared to nondiabetic controls (n=5) or peripheral retinal regions of the same retinas (P<0.01 in both cases). Here we introduce a new approach for early diagnosis of DR and VEGFR-2 as a molecular marker. VEGFR-2 could become a key diagnostic target, one that might help to prevent retinal vascular leakage and proliferation in diabetic patients. © FASEB.

Visual BOLD Response in Late Blind Subjects with Argus II Retinal Prosthesis.

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E Castaldi

2016-10-01

Full Text Available Retinal prosthesis technologies require that the visual system downstream of the retinal circuitry be capable of transmitting and elaborating visual signals. We studied the capability of plastic remodeling in late blind subjects implanted with the Argus II Retinal Prosthesis with psychophysics and functional MRI (fMRI. After surgery, six out of seven retinitis pigmentosa (RP blind subjects were able to detect high-contrast stimuli using the prosthetic implant. However, direction discrimination to contrast modulated stimuli remained at chance level in all of them. No subject showed any improvement of contrast sensitivity in either eye when not using the Argus II. Before the implant, the Blood Oxygenation Level Dependent (BOLD activity in V1 and the lateral geniculate nucleus (LGN was very weak or absent. Surprisingly, after prolonged use of Argus II, BOLD responses to visual input were enhanced. This is, to our knowledge, the first study tracking the neural changes of visual areas in patients after retinal implant, revealing a capacity to respond to restored visual input even after years of deprivation.

ℓ0TV: A new method for image restoration in the presence of impulse noise

KAUST Repository

Yuan, Ganzhao

2015-06-02

Total Variation (TV) is an effective and popular prior model in the field of regularization-based image processing. This paper focuses on TV for image restoration in the presence of impulse noise. This type of noise frequently arises in data acquisition and transmission due to many reasons, e.g. a faulty sensor or analog-to-digital converter errors. Removing this noise is an important task in image restoration. State-of-the-art methods such as Adaptive Outlier Pursuit(AOP), which is based on TV with L02-norm data fidelity, only give sub-optimal performance. In this paper, we propose a new method, called L0T V -PADMM, which solves the TV-based restoration problem with L0-norm data fidelity. To effectively deal with the resulting non-convex nonsmooth optimization problem, we first reformulate it as an equivalent MPEC (Mathematical Program with Equilibrium Constraints), and then solve it using a proximal Alternating Direction Method of Multipliers (PADMM). Our L0TV-PADMM method finds a desirable solution to the original L0-norm optimization problem and is proven to be convergent under mild conditions. We apply L0TV-PADMM to the problems of image denoising and deblurring in the presence of impulse noise. Our extensive experiments demonstrate that L0TV-PADMM outperforms state-of-the-art image restoration methods.

Brain MR Image Restoration Using an Automatic Trilateral Filter With GPU-Based Acceleration.

Science.gov (United States)

Chang, Herng-Hua; Li, Cheng-Yuan; Gallogly, Audrey Haihong

2018-02-01

Noise reduction in brain magnetic resonance (MR) images has been a challenging and demanding task. This study develops a new trilateral filter that aims to achieve robust and efficient image restoration. Extended from the bilateral filter, the proposed algorithm contains one additional intensity similarity funct-ion, which compensates for the unique characteristics of noise in brain MR images. An entropy function adaptive to intensity variations is introduced to regulate the contributions of the weighting components. To hasten the computation, parallel computing based on the graphics processing unit (GPU) strategy is explored with emphasis on memory allocations and thread distributions. To automate the filtration, image texture feature analysis associated with machine learning is investigated. Among the 98 candidate features, the sequential forward floating selection scheme is employed to acquire the optimal texture features for regularization. Subsequently, a two-stage classifier that consists of support vector machines and artificial neural networks is established to predict the filter parameters for automation. A speedup gain of 757 was reached to process an entire MR image volume of 256 × 256 × 256 pixels, which completed within 0.5 s. Automatic restoration results revealed high accuracy with an ensemble average relative error of 0.53 ± 0.85% in terms of the peak signal-to-noise ratio. This self-regulating trilateral filter outperformed many state-of-the-art noise reduction methods both qualitatively and quantitatively. We believe that this new image restoration algorithm is of potential in many brain MR image processing applications that require expedition and automation.

Detection of retinal changes from illumination normalized fundus images using convolutional neural networks

NARCIS (Netherlands)

Adal, K.M.; Van Etten, Peter G.; Martinez, Jose P; Rouwen, Kenneth; Vermeer, K.A.; van Vliet, L.J.; Armato, Samuel G.; Petrick, Nicholas A.

2017-01-01

Automated detection and quantification of spatio-temporal retinal changes is an important step to objectively assess disease progression and treatment effects for dynamic retinal diseases such as diabetic retinopathy (DR). However, detecting retinal changes caused by early DR lesions such as

The Role of Fundus Autofluorescence in Late-Onset Retinitis Pigmentosa (LORP) Diagnosis

Science.gov (United States)

Lee, Tamara J.; Hwang, John C.; Chen, Royce W. S.; Lima, Luiz H.; Wang, Nan-Kai; Tosi, Joaquin; Freund, K. Bailey; Yannuzzi, Lawrence A.; Tsang, Stephen H.

2015-01-01

Purpose To demonstrate the utility and characteristics of fundus autofluorescence in late-onset retinitis pigmentosa. Methods Observational case series. Patients diagnosed with late-onset retinitis pigmentosa were identified retrospectively in an institutional setting. Twelve eyes of six patients were identified and medical records were reviewed. Results All patients presented with slowly progressive peripheral field loss and initial clinical examination revealed only subtle retinal changes. There was a notable lack of intraretinal pigment migration in all patients. Five out of six patients underwent magnetic resonance imaging of the brain to rule out intracranial processes and all were referred from another ophthalmologist for further evaluation. Fundus autofluorescence was ultimately employed in all patients and revealed more extensive retinal pathology than initially appreciated on clinical examination. Fundus autofluorescence directed the workup toward a retinal etiology in all cases and led to the eventual diagnosis of late-onset retinitis pigmentosa through electroretinogram testing. Conclusion Fundus autofluorescence may be a more sensitive marker for retinal pathology than stereo fundus biomicroscopy alone in late-onset retinitis pigmentosa. Early use of fundus autofluorescence imaging in the evaluation of patients with subtle retinal lesions and complaints of peripheral field loss may be an effective strategy for timely and cost-efficient diagnosis. PMID:23899229

Elastic models: a comparative study applied to retinal images.

Science.gov (United States)

Karali, E; Lambropoulou, S; Koutsouris, D

2011-01-01

In this work various methods of parametric elastic models are compared, namely the classical snake, the gradient vector field snake (GVF snake) and the topology-adaptive snake (t-snake), as well as the method of self-affine mapping system as an alternative to elastic models. We also give a brief overview of the methods used. The self-affine mapping system is implemented using an adapting scheme and minimum distance as optimization criterion, which is more suitable for weak edges detection. All methods are applied to glaucomatic retinal images with the purpose of segmenting the optical disk. The methods are compared in terms of segmentation accuracy and speed, as these are derived from cross-correlation coefficients between real and algorithm extracted contours and segmentation time, respectively. As a result, the method of self-affine mapping system presents adequate segmentation time and segmentation accuracy, and significant independence from initialization.

Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets

KAUST Repository

Lenzen, F.; Lellmann, J.; Becker, F.; Schnö rr, C.

2014-01-01

© 2014 Society for Industrial and Applied Mathematics. We consider a class of quasi-variational inequalities (QVIs) for adaptive image restoration, where the adaptivity is described via solution-dependent constraint sets. In previous work we studied

Characterization of cytochrome c as marker for retinal cell degeneration by uv/vis spectroscopic imaging

Science.gov (United States)

Hollmach, Julia; Schweizer, Julia; Steiner, Gerald; Knels, Lilla; Funk, Richard H. W.; Thalheim, Silko; Koch, Edmund

2011-07-01

Retinal diseases like age-related macular degeneration have become an important cause of visual loss depending on increasing life expectancy and lifestyle habits. Due to the fact that no satisfying treatment exists, early diagnosis and prevention are the only possibilities to stop the degeneration. The protein cytochrome c (cyt c) is a suitable marker for degeneration processes and apoptosis because it is a part of the respiratory chain and involved in the apoptotic pathway. The determination of the local distribution and oxidative state of cyt c in living cells allows the characterization of cell degeneration processes. Since cyt c exhibits characteristic absorption bands between 400 and 650 nm wavelength, uv/vis in situ spectroscopic imaging was used for its characterization in retinal ganglion cells. The large amount of data, consisting of spatial and spectral information, was processed by multivariate data analysis. The challenge consists in the identification of the molecular information of cyt c. Baseline correction, principle component analysis (PCA) and cluster analysis (CA) were performed in order to identify cyt c within the spectral dataset. The combination of PCA and CA reveals cyt c and its oxidative state. The results demonstrate that uv/vis spectroscopic imaging in conjunction with sophisticated multivariate methods is a suitable tool to characterize cyt c under in situ conditions.

Research on Adaptive Optics Image Restoration Algorithm by Improved Expectation Maximization Method

OpenAIRE

Zhang, Lijuan; Li, Dongming; Su, Wei; Yang, Jinhua; Jiang, Yutong

2014-01-01

To improve the effect of adaptive optics images’ restoration, we put forward a deconvolution algorithm improved by the EM algorithm which joints multiframe adaptive optics images based on expectation-maximization theory. Firstly, we need to make a mathematical model for the degenerate multiframe adaptive optics images. The function model is deduced for the points that spread with time based on phase error. The AO images are denoised using the image power spectral density and support constrain...

Retinal Oximetry with Scanning Laser Ophthalmoscope in Infants.

Directory of Open Access Journals (Sweden)

Wouter B Vehmeijer

Full Text Available Dual wavelength retinal oximetry has been developed for adults, but is not available for infants. Retinal oximetry may provide insight into the pathophysiology of oxygen-mediated diseases like retinopathy of prematurity. More insight in the oxygen metabolism of the retina in infants may provide valuable clues for better understanding and subsequent prevention or treatment of the disease. The measurements of oxygen saturation are obtained with two fundus images simultaneously captured in two different wavelengths of light. The comparison in light absorption of oxygenated and deoxygenated hemoglobin can be used to estimate the oxygen saturation within the retinal vessels by means of a software algorithm. This study aims to make retinal oximetry available for neonates. The first step towards estimating retinal oxygen saturation is determining the optical density ratio. Therefore, the purpose of this study is to image healthy newborn infants with a scanning laser ophthalmoscope and determine the optical density ratio for retinal oximetry analysis.Images of the retina of full-term healthy infants were obtained with an SLO, Optomap 200Tx (Optos, with two laser wavelengths (532nm and 633nm. The infant lay face down on the lower arm of the parent, while the parent supported the chest and chin with one hand, and stabilized the back with the other hand. No mydriatics or eyelid specula were used during this study. The images were analyzed with modified Oxymap Analyzer software for calculation of the Optical Density Ratio (ODR and vessel width. The ODR is inversely and approximately linearly related to the oxygen saturation. Measurements were included from the superotemporal vessel pair. A paired t-test was used for statistical analysis.Fifty-nine infants, (58% female, were included with mean gestational age of 40 ± 1.3 weeks (mean ± SD and mean post-natal age of 16 ± 4.8 days. A total of 28 images were selected for retinal oximetry analysis. The ODR was

Automatic detection of retinal anatomy to assist diabetic retinopathy screening

Science.gov (United States)

Fleming, Alan D.; Goatman, Keith A.; Philip, Sam; Olson, John A.; Sharp, Peter F.

2007-01-01

Screening programmes for diabetic retinopathy are being introduced in the United Kingdom and elsewhere. These require large numbers of retinal images to be manually graded for the presence of disease. Automation of image grading would have a number of benefits. However, an important prerequisite for automation is the accurate location of the main anatomical features in the image, notably the optic disc and the fovea. The locations of these features are necessary so that lesion significance, image field of view and image clarity can be assessed. This paper describes methods for the robust location of the optic disc and fovea. The elliptical form of the major retinal blood vessels is used to obtain approximate locations, which are refined based on the circular edge of the optic disc and the local darkening at the fovea. The methods have been tested on 1056 sequential images from a retinal screening programme. Positional accuracy was better than 0.5 of a disc diameter in 98.4% of cases for optic disc location, and in 96.5% of cases for fovea location. The methods are sufficiently accurate to form an important and effective component of an automated image grading system for diabetic retinopathy screening.

Automatic detection of retinal anatomy to assist diabetic retinopathy screening

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Fleming, Alan D [Biomedical Physics, University of Aberdeen, Aberdeen, AB25 2ZD (United Kingdom); Goatman, Keith A [Biomedical Physics, University of Aberdeen, Aberdeen, AB25 2ZD (United Kingdom); Philip, Sam [Grampian Diabetes Retinal Screening Programme, Woolmanhill Hospital, Aberdeen, AB25 1LD (United Kingdom); Olson, John A [Grampian Diabetes Retinal Screening Programme, Woolmanhill Hospital, Aberdeen, AB25 1LD (United Kingdom); Sharp, Peter F [Biomedical Physics, University of Aberdeen, Aberdeen, AB25 2ZD (United Kingdom)

2007-01-21

Screening programmes for diabetic retinopathy are being introduced in the United Kingdom and elsewhere. These require large numbers of retinal images to be manually graded for the presence of disease. Automation of image grading would have a number of benefits. However, an important prerequisite for automation is the accurate location of the main anatomical features in the image, notably the optic disc and the fovea. The locations of these features are necessary so that lesion significance, image field of view and image clarity can be assessed. This paper describes methods for the robust location of the optic disc and fovea. The elliptical form of the major retinal blood vessels is used to obtain approximate locations, which are refined based on the circular edge of the optic disc and the local darkening at the fovea. The methods have been tested on 1056 sequential images from a retinal screening programme. Positional accuracy was better than 0.5 of a disc diameter in 98.4% of cases for optic disc location, and in 96.5% of cases for fovea location. The methods are sufficiently accurate to form an important and effective component of an automated image grading system for diabetic retinopathy screening.

Automatic detection of retinal anatomy to assist diabetic retinopathy screening

International Nuclear Information System (INIS)

Fleming, Alan D; Goatman, Keith A; Philip, Sam; Olson, John A; Sharp, Peter F

2007-01-01

Screening programmes for diabetic retinopathy are being introduced in the United Kingdom and elsewhere. These require large numbers of retinal images to be manually graded for the presence of disease. Automation of image grading would have a number of benefits. However, an important prerequisite for automation is the accurate location of the main anatomical features in the image, notably the optic disc and the fovea. The locations of these features are necessary so that lesion significance, image field of view and image clarity can be assessed. This paper describes methods for the robust location of the optic disc and fovea. The elliptical form of the major retinal blood vessels is used to obtain approximate locations, which are refined based on the circular edge of the optic disc and the local darkening at the fovea. The methods have been tested on 1056 sequential images from a retinal screening programme. Positional accuracy was better than 0.5 of a disc diameter in 98.4% of cases for optic disc location, and in 96.5% of cases for fovea location. The methods are sufficiently accurate to form an important and effective component of an automated image grading system for diabetic retinopathy screening

Automatic detection of retinal anatomy to assist diabetic retinopathy screening.

Science.gov (United States)

Fleming, Alan D; Goatman, Keith A; Philip, Sam; Olson, John A; Sharp, Peter F

2007-01-21

Screening programmes for diabetic retinopathy are being introduced in the United Kingdom and elsewhere. These require large numbers of retinal images to be manually graded for the presence of disease. Automation of image grading would have a number of benefits. However, an important prerequisite for automation is the accurate location of the main anatomical features in the image, notably the optic disc and the fovea. The locations of these features are necessary so that lesion significance, image field of view and image clarity can be assessed. This paper describes methods for the robust location of the optic disc and fovea. The elliptical form of the major retinal blood vessels is used to obtain approximate locations, which are refined based on the circular edge of the optic disc and the local darkening at the fovea. The methods have been tested on 1056 sequential images from a retinal screening programme. Positional accuracy was better than 0.5 of a disc diameter in 98.4% of cases for optic disc location, and in 96.5% of cases for fovea location. The methods are sufficiently accurate to form an important and effective component of an automated image grading system for diabetic retinopathy screening.