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Diabetic Retinopathy (DR) is the first cause of blindness in working-age adults (20-74 years old), but if prompt diagnosis is made, 80% of DR complications can be delayed or prevented. Smartphone and wide-field fundus photography have been showing promising results for DR screening; however, efforts continue to get better fundus camera devices regarding image quality, FOV, affordability, and accessibility that could help prevent blindness through prompt diagnosis. Here we show the design, implementation, and characterization of a wide-field smartphone-based fundus camera prototype (TRL 4) to be used as a point-of-care device for DR screening. What stands our design apart is the use of a smartphone's macro-camera with a high diopter ophthalmic loupe for wide-field in a single shot, our cross-polarized ring for reflection-free fundus images, and the two-handed mechanical design to enhance stability. The presented prototype is safe (Group 1 according to ISO 15004-2), easy to use (80° static FOV), affordable (500 USD <), portable (hand-held, 280 x 90 x 90 mm and 410 gr), and reliable (46 lp/mm central spatial resolution at fundus). The prototype represents an ideal alternative for DR screening at point-of-care and, by incorporating the appropriate Al and teleophthalmology tools, a potential improvement in blindness prevention in the diabetic population. [ABSTRACT FROM AUTHOR]

Our study aimed to assess the role of a hand-held fundus camera and artificial intelligence (AI)-based grading system in diabetic retinopathy (DR) screening and determine its diagnostic accuracy in detecting DR compared with clinical examination and a standard fundus camera. This cross-sectional instrument validation study, as a part of the International Diabetes Federation (IDF) Diabetic Retinopathy Screening Project, included 160 patients (320 eyes) with type 2 diabetes (T2DM). After the standard indirect slit-lamp fundoscopy, each patient first underwent fundus photography with a standard 45° camera VISUCAM Zeiss and then with a hand-held camera TANG (Shanghai Zhi Tang Health Technology Co., Ltd.). Two retina specialists independently graded the images taken with the standard camera, while the images taken with the hand-held camera were graded using the DeepDR system and an independent IDF ophthalmologist. The three screening methods did not differ in detecting moderate/severe nonproliferative and proliferative DR. The area under the curve, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, kappa (ĸ) agreement, diagnostic odds ratio, and diagnostic effectiveness for a hand-held camera compared to clinical examination were 0.921, 89.1%, 100%, 100%, 91.4%, infinity, 0.11, 0.86, 936.48, and 94.9%, while compared to the standard fundus camera were 0.883, 83.2%, 100%, 100%, 87.3%, infinity, 0.17, 0.78, 574.6, and 92.2%. The results of our study suggest that fundus photography with a hand-held camera and AI-based grading system is a short, simple, and accurate method for the screening and early detection of DR, comparable to clinical examination and fundus photography with a standard camera. [ABSTRACT FROM AUTHOR]

In this study, we describe the development of a compact NIR multispectral imaging sensor for use in glare-free NIR color fundus cameras. Integrating NIR technology into a fundus camera offers significant advantages over conventional RGB imaging using visible illumination, as it enables the glare-free capture of fundus images with minimal patient discomfort. The specifications necessary for a glare-free NIR color fundus camera were evaluated on the basis of factors such as pixel pitch size, pixel array layout, and multilayer interference filter design, in accordance with the camera's intended purpose. While multilayer interference filters were deposited on a glass substrate and bonded with the sensor chip in a 7.5 µm pixel pitch in a previous study, we propose an NIR multispectral imaging sensor directly depositing the interference filters on the wafer in a narrower 4 µm pixel pitch. In addition, the fabrication process for directly depositing NIR multispectral filters on the sensor wafer was proposed. The fabricated NIR multispectral imaging sensor was analyzed against the intended design. Finally, an NIR multispectral imaging sensor was installed on a glare-free NIR color fundus camera, and it was confirmed that the resulting camera is capable of providing medically relevant and meaningful information. [ABSTRACT FROM AUTHOR]

Diabetic retinopathy (DR) is vision impairment and a life-threatening condition for diabetic patients. Especially type II diabetic people have higher chances of getting retinal problems. Hence, early prediction of DR is necessary for preventing the diabetic patients from vision impairment. The main aim of this feasibility study is to identify the most critical risk features that could lead to diabetic retinopathy. This study investigated type II diabetic patients' socio-analytical, diabetes, behavioral, and clinical risk factors. We conducted a self-individual questionnaire session for all participants. Our questionnaire asked about the reliability of results, feeling comfortable during the screening test, willingness to participate in future screenings, overall perspective, and satisfaction with the DR screening test. We proposed a random forest model for predicting the prevalence of DR risk among diabetics. Further explanations of the model were conducted using more robust SHAP eXplainable Artificial Intelligence (XAI) tools. The SHAP method makes it possible to understand how input variables interact with their representative output records, as well as how input variables are ranked. In addition, various descriptive and inferential statistical analyses were performed on the data and evaluated the significant relationship between the factors discussed above via hypothesis testing. This feasibility study involved 172 type II diabetic patients (73 males and 99 females). Therefore, we found that 81 (47.09%) out of 172 participants had referable DR. The average age of the patients was determined as 55.08, with a standard deviation of ± 9.770 (ranging from 40 to 79). Type II patients were affected by mild, moderate, severe, and advanced proliferative diabetic retinopathy (PDR) stages with 23.83%, 13.95%, 5.81%, and 3.48%, respectively, of the total samples. The developed RF model obtained high accuracy of 94.9% using clinical dataset. Our results showed that the formation of tiny microminiature lesions was noticeable in type II diabetic patients with aged people, abnormal blood glucose levels, and prolonged diabetes duration. [ABSTRACT FROM AUTHOR]

Purpose: There is a clinical need for a cost-effective, reliable, easy-to-use, and portable retinal photography. The use of smartphone fundus photography for documentation of retinal changes in resource-limited settings, where retinal imaging was not previously possible, is studied here. The introduction of smartphone-based retinal imaging has resulted in the increase in available technologies for fundus photography. On account of the cost, fundus cameras are not readily available in ophthalmic practice in developing countries. Because smartphones are readily available, easy to use, and also portable, they present a low-cost alternative method in resource-limited settings. The aim is to explore the use of smartphones (iphones) for retinal imaging in resource-limited settings. Methods: A smartphone (iphone) was used to acquire retinal images with the use of +20 D lens in patients with dilated pupils by activating the video mode of the camera. Results: Clear retinal images were obtained in different clinical conditions in adults and children, including branch retinal vein occlusion with fibro-vascular proliferation, choroidal neo-vascular membranes, presumed ocular toxoplasmosis, diabetic retinopathy, retinoblastoma, ocular albinism, and hypertensive retinopathy. Conclusion: New inexpensive, portable, easy-to-operate cameras have revolutionized retinal imaging and screening programs and play an innovative role in research, education, and information sharing. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate differences in acquisition time, peripheral extension, and chromaticity between 3 different commercialized ultra-wide-field (UWF) fundus cameras. Methods: Patients were prospectively enrolled from 07/2021 to 11/2021. Patients underwent fundus photography with the following scanning protocols: (1) single shot with Silverstone (Optos, California), two-shot montage with Clarus 500 (Carl Zeiss, Dublin, CA), and three-shot montage with iCare EIDON FA with UWF module (CenterVue Spa, a company of iCare Finland Oy; Vantaa, Finland). Acquisition time was calculated as the interval between the beginning and the end of the acquisition. Peripheral extension was quantified as the average ratio between the total retinal pixel area and the optic nerve head (ONH) pixel area. The average chromaticity of all pixels in the red–green–blue (RGB) space was calculated. Results: Twenty-three eyes of 13 prospectively enrolled healthy controls were included in the study. Optos Silverstone had a higher total retina area/ONH area ratio (509.1 [480.9;559.3]) compared to Zeiss Clarus (442.0 [431.9;510.5], p = 0.02) and iCare EIDON (369.7 [345.3;387.8], p < 0.0001). Silverstone demonstrated the shortest acquisition time (median [interquartile range]: 32 [20;58.5] s) compared to Zeiss Clarus (42 [28.5;53.5] s, p = 0.6733) and iCare EIDON (72 [68.5;78] s, p = 0.0003). iCare EIDON demonstrated the lowest variability of acquisition time (9.5 s), compared to Zeiss Clarus (25 s) and Optos Silverstone (38.5 s). A statistically significant difference was found in the RGB distribution between each of the 3 devices (p < 0.001). iCare EIDON demonstrated an average barycenter position (RGB = [0.412, 0.314, 0.275]) that represented the best color balance of the image. Zeiss Clarus had a noticeable red shift at the expense of the blue and green channels (RGB = [0.515, 0.294, 0.191]). Optos Silverstone showed an absence of the blue channel (RGB = [0.621, 0.372, 0.007]) which results in a distortion of the color of the image. Conclusion: Optos Silverstone and Zeiss Clarus required less time than iCare EIDON to acquire a comparable size image and captured larger areas of the retina than iCare EIDON. iCare EIDON provided more color-balanced retinal images with greater richness of color content than the other two devices. [ABSTRACT FROM AUTHOR]

Amro Omari,1,2 Momin Samad,3 Saaquib R Bakhsh,1,2 Jahan Tajran,4 George A Williams1,2 1Beaumont Eye Institute, Royal Oak, MI, USA; 2Oakland University William Beaumont School of Medicine, Rochester, MI, USA; 3Michigan State College of Human Medicine, Grand Rapids, MI, USA; 4Wayne State University School of Medicine, Detroit, MI, USACorrespondence: Amro Omari, Beaumont Eye Institute, 3535 West 13 Mile Road Suite #555, Royal Oak, MI, 48073, USA, Tel +1 248-551-2020, Email Amro.omari@beaumont.orgBackground and Objective: To assess the use of a smartphone-based fundus camera in diagnosing acute posterior segment disease in the emergency room (ER) of an academic center, where standard fundus cameras are currently unavailable.Study Design/Patients and Methods: Images were obtained on 10 eyes with various types of posterior segment pathology. These were analyzed retrospectively by 35 reviewers (21 residents and 14 attending physicians). Accuracy of diagnosis was compared to in-office fundus photography.Results: The average probability of correct diagnosis was over 78%. There was no difference between resident and attending reviewers, except for one of the vitreous hemorrhage cases where residents performed better (p=0.039).Conclusion: Smartphone-based cameras are effective in screening for ocular diseases in the ER of academic centers, where residents and fellows are often the first providers to see various types of vision and life-threatening pathology.Keywords: fundus camera, emergency room, posterior segment, smartphone, retina

Introduction: Onchocerciasis is the world's second leading cause of infectious blindness and remains a major problem in parts of Africa. In light of the efforts targeted towards improving ongoing elimination program, this study assessed onchocerca-induced visual impairments in Gashaka local government areas (LGA) in Taraba State, north-eastern Nigeria. Methods: In 2019, we recruited 158 consenting visually impaired persons across three communities in Garbabi ward of Gashaka LGA. To avoid confusion with co-endemic trachoma, the integrity of the tarsal conjunctiva, eyelashes were assessed using direct light. The anterior segment of the eye was also examined using a torchlight with oblique illumination. However, the posterior segment of the eye was assessed using a fundus camera. Two photographic images for the left and right eye of each participant were captured using the clinical fundus camera. The photographic eye images that were too dark were discarded, and only clear images were analyzed by two ophthalmologists. An ocular manifestation report was recorded for each participant following consensus between the ophthalmologists. Results: Of the 316 photographic eye images, almost half 146 (46.2%) from 73 participants were just too destroyed for light to penetrate and was not included in the analysis. Only 170 from 85 participants were clear and examinable. A total of 33 (39%) participants had chorioretinitis suggestive of onchocerciasis, including 22(25.9%) with chorio-retinal atrophy, 7(8.2%) and 4(4.7%) had chorioretinal atrophy in combination with early cataract and signs of trachoma respectively. In addition, 3(3.5%) of the participant had eye images which showed lens opacities, 1(1.2%) showed signs of keratoconus and 1(1.2%) showed a scared and pigmented cornea, possibly due to onchocerciasis. Furthermore, 28 (32.9%) had some ill-defined changes and 19 (22.4%) showed poorly defined chorio-retinal atrophy. Conclusion: In a bid to sustain MDA gains towards elimination of onchocerciasis, this work highlights the need for continuous assessment of onchocerciasis induced visual impairment, strengthening of ivermectin delivery and optimizing compliance and patient care among affected populations. These would require resource acquisition and local capacity building. Our preliminary findings call for further operational research on ocular morbidity as well as future stakeholders' consultations in this important and understudied area.

Our study aimed to assess the role of a hand-held fundus camera and artificial intelligence (AI)-based grading system in diabetic retinopathy (DR) screening and determine its diagnostic accuracy in detecting DR compared with clinical examination and a standard fundus camera. This cross-sectional instrument validation study, as a part of the International Diabetes Federation (IDF) Diabetic Retinopathy Screening Project, included 160 patients (320 eyes) with type 2 diabetes (T2DM). After the standard indirect slit-lamp fundoscopy, each patient first underwent fundus photography with a standard 45° camera VISUCAM Zeiss and then with a hand-held camera TANG (Shanghai Zhi Tang Health Technology Co., Ltd.). Two retina specialists independently graded the images taken with the standard camera, while the images taken with the hand-held camera were graded using the DeepDR system and an independent IDF ophthalmologist. The three screening methods did not differ in detecting moderate/severe nonproliferative and proliferative DR. The area under the curve, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, kappa (ĸ) agreement, diagnostic odds ratio, and diagnostic effectiveness for a hand-held camera compared to clinical examination were 0.921, 89.1%, 100%, 100%, 91.4%, infinity, 0.11, 0.86, 936.48, and 94.9%, while compared to the standard fundus camera were 0.883, 83.2%, 100%, 100%, 87.3%, infinity, 0.17, 0.78, 574.6, and 92.2%. The results of our study suggest that fundus photography with a hand-held camera and AI-based grading system is a short, simple, and accurate method for the screening and early detection of DR, comparable to clinical examination and fundus photography with a standard camera.

Purpose: We aim to present effective and computer aided diagnostics in the field of ophthalmology and improve eye health. This study aims to create an automated deep learning based system for categorizing fundus images into three classes: normal, macular degeneration and tessellated fundus for the timely recognition and treatment of diabetic retinopathy and other diseases.Methods: A total of 1,032 fundus images were collected from 516 patients using fundus camera from Health Management Center, Shenzhen University General Hospital Shenzhen University, Shenzhen 518055, Guangdong, China. Then, Inception V3 and ResNet-50 deep learning models are used to classify fundus images into three classes, Normal, Macular degeneration and tessellated fundus for the timely recognition and treatment of fundus diseases.Results: The experimental results show that the effect of model recognition is the best when the Adam is used as optimizer method, the number of iterations is 150, and 0.00 as the learning rate. According to our proposed approach we, achieved the highest accuracy of 93.81% and 91.76% by using ResNet-50 and Inception V3 after fine-tuned and adjusted hyper parameters according to our classification problem.Conclusion: Our research provides a reference to the clinical diagnosis or screening for diabetic retinopathy and other eye diseases. Our suggested computer aided diagnostics framework will prevent incorrect diagnoses caused by the low image quality and individual experience, and other factors. In future implementations, the ophthalmologists can implement more advanced learning algorithms to improve the accuracy of diagnosis.

OBJECTIVE: The aim of this study was to evaluate the ocular health of care-center residents with disabilities who have difficulty accessing health care using a novel smartphone-adapted fundus camera device, and to compare the results to age- and gender- matched health subjects. PATIENTS AND METHODS: In this study, 47 care-center residents with disabilities were investigated between October 1, 2021, and December 31, 2021. A control group was made up of healthy volunteers. All participants underwent a comprehensive ocular exam, which included measuring visual acuity and assessing dry eye with Schirmer and tear break-up time tests. The posterior segment was examined using a smartphone-adapted fundus camera. The data gathered was compared with statistical significance between the two groups. RESULTS: The mean ages of disabled and healthy participants were 59.7±15.2 and 56.6±15.0 years, respectively (p=0.305). While 11.1% of the 36 visually impaired participants were legally blind, the percentage among healthy subjects was only 3.7% (p=0.168). In comparison to healthy participants, disabled people had statistically significantly higher rates of dry eye (27.7%), senile macular degeneration (23.4%), and cataracts (29.8%) (p<0.05). CONCLUSIONS: Screening for ocular health with a novel smartphone-adapted fundus camera revealed significantly higher rates of various ocular diseases in care center disabled residents. Given technological progress, remote control method-assisted ocular exams appear to be potentially feasible and clinically beneficial. This could allow trained allied health personnel to perform ocular health screenings without the need to transport a disabled person to the hospital. Thus, diagnosis and follow- up of various chronic ocular diseases may be properly organized. [ABSTRACT FROM AUTHOR]

Despite evidence that non-mydriatic fundus cameras are beneficial in non-ophthalmic settings, they are only available in a minority of hospitals in the US. The lag from research-based evidence to change in clinical practice highlights the complexities of implementation of new technology and practice. We describe the steps used to implement successfully a non-mydriatic ocular fundus camera combined with optical coherence tomography (OCT) in a general emergency department (ED) using Kotter's 8-Step Change Model. We prospectively collected the number of trained personnel in the ED, the number of imaging studies obtained each week during the first year following implementation, and we documented major achievements each month, as well as outcome measures, barriers to implementation and possible solutions. Between 12 and 42 patients were imaged per week, resulting in a total of 1274 patients imaged demonstrating sustained usage of non-mydriatic fundus camera/OCT in the ED one year after implementation. The implementation process was contingent upon multidisciplinary collaboration, extensive communication, coordinated training of staff, and continuous motivation. The future will likely include the use of artificial intelligence deep learning systems for automated interpretation of ocular imaging as an immediate diagnostic aid for ED or other non-eye care providers., Competing Interests: Declaration of Competing Interest The authors report no proprietary or commercial interest in any product mentioned or concept discussed in this article., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The eye, the photoreceptive organ used to perceive the external environment, is of great importance to humans. It has been proven that some diseases in humans are accompanied by fundus changes; therefore, the health status of people may be interpreted from retinal images. However, the human eye is not a perfect refractive system for the existence of ocular aberrations. These aberrations not only affect the ability of human visual discrimination and recognition, but restrict the observation of the fine structures of human eye and reduce the possibility of exploring the mechanisms of eye disease. Adaptive optics (AO) is a technique that corrects optical wavefront aberrations. Once integrated into ophthalmoscopes, AO enables retinal imaging at the cellular level. This paper illustrates the principle of AO in correcting wavefront aberrations in human eyes, and then reviews the applications and advances of AO in ophthalmology, including the adaptive optics fundus camera (AO-FC), the adaptive optics scanning laser ophthalmoscope (AO-SLO), the adaptive optics optical coherence tomography (AO-OCT), and their combined multimodal imaging technologies. The future development trend of AO in ophthalmology is also prospected. [ABSTRACT FROM AUTHOR]

Abstract Fundus autofluorescence (FAF) has allowed in vivo mapping of retinal metabolic derangements and structural changes not possible with conventional color imaging. Incident light is absorbed by molecules in the fundus, which are excited and in turn emit photons of specific wavelengths that are captured and processed by a sensor to create a metabolic map of the fundus. Studies on the growing number of FAF platforms has shown each may be suited to certain clinical scenarios. Scanning laser ophthalmoscopes, fundus cameras, and modifications of these each have benefits and drawbacks that must be considered before and after imaging to properly interpret the images. Emerging clinical evidence has demonstrated the usefulness of FAF in diagnosis and management of an increasing number of chorioretinal conditions, such as age-related macular degeneration, central serous chorioretinopathy, retinal drug toxicities, and inherited retinal degenerations such as retinitis pigmentosa and Stargardt disease. This article reviews commercial imaging platforms, imaging techniques, and clinical applications of FAF.

Diagnosis by ocular fundus imaging plays a key role in the monitoring, detection, and diagnosis of several diseases including eye-related, hypertensive, and cardiovascular diseases as well as the detection of brain microvascular and neuronal pathology. The spectral detection of the fundus in the near-infrared (NIR) region can be used to analyze the composition and content of the fundus substance. The aim of this study was to develop a multichannel bandpass filter, which can be assembled on a CMOS image sensor installed in a fundus camera, to realize spectral imaging. We designed the filter in the NIR region according to interference filter theory and fabricated it by sputtering, lithography, and etching. The images acquired by the image sensor with the fabricated bandpass filter confirmed that the pixel values were comparable to the values calculated from spectrometer measurements. In an experimental validation, the number of measurement wavelengths was increased by applying the incident angle dependence of the interference filter. Each fabricated filter had a relatively wide transmittance band for spectral detection, broadening the spectrum curve. Moreover, a high-resolution spectrum was reconstructed using the developed algorithm. The spectrum reconstructed by the proposed filter had a 15% average relative error over the entire wavelength range of interest. [ABSTRACT FROM AUTHOR]

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In this article, we introduce a very low-price smartphone fundus camera device with basic amenities. It has become very fruitful toward undergraduate teaching at the bedside or in the outpatient department, especially where there are no facilities for the fundus camera unit. A fundus camera unit is an essential part of retina clinic, and it is very costly. Fundus photographs are very essential for disease diagnosis, its follow-up, and for disease monitoring. It cannot be carried to the camp side. Commercially, available fundus cameras are the alternative to this, but again very costly. Almost zero price this innovation helps the students to see the fundus pathologies with their own eyes and make them more clinically oriented.

This review starts with a brief history and description of adaptive optics (AO) technology, followed by a showcase of the latest capabilities of AO systems for imaging the human retina and an extensive review of the literature on where AO is being used clinically. The review concludes with a discussion on future directions and guidance on usage and interpretation of images from AO systems for the eye.

Diabetic retinopathy (DR) is a leading cause of blindness among adults and the numbers are projected to rise. There have been dramatic advances in the field of retinal imaging since the first fundus image was captured by Jackman and Webster in 1886. The currently available imaging modalities in the management of DR include fundus photography, fluorescein angiography, autofluorescence imaging, optical coherence tomography, optical coherence tomography angiography, and near-infrared reflectance imaging. These images are obtained using traditional fundus cameras, widefield fundus cameras, handheld fundus cameras, or smartphone-based fundus cameras. Fluorescence lifetime ophthalmoscopy, adaptive optics, multispectral and hyperspectral imaging, and multicolor imaging are the evolving technologies which are being researched for their potential applications in DR. Telemedicine has gained popularity in recent years as remote screening of DR has been made possible. Retinal imaging technologies integrated with artificial intelligence/deep-learning algorithms will likely be the way forward in the screening and grading of DR. We provide an overview of the current and upcoming imaging modalities which are relevant to the management of DR. [ABSTRACT FROM AUTHOR]

Retinal blood vessel segmentation plays an important part in the early diagnosis and treatment of eye disease. It is a tool for ophthalmologists. Many diseases can be identified by examining manifestations and images of blood vessels, including diabetic retinopathy, retinopathy of prematurity, age-related macular degeneration, retinopathy due to hypertension, glaucoma and others. Early detection allows physicians to provide patients with effective treatment, while in the opposite case, the late detection of retinal disease can ultimately lead to blindness. One of the indices when examining the retina is an evaluation of blood vessels based on tortuosity, i.e. the degree of curvature of blood vessels. This article presents a comprehensive overview of all segmentation techniques for retinal blood vessel extraction from images taken with a fundus camera in adults and older children or with a RetCam fundus camera in new-borns and younger children over the last 10 years. An integral part of this review is a comprehensive overview with information on all available public and private databases with retinal images. The review includes an evaluation of segmentation techniques based on objectivization parameters, including information on all objectivization parameters used in this article. As already mentioned, the degree of curvature of retinal blood vessels is used to classify severity of blood vessels tortuosity. There is no uniform metric for determining tortuosity, but this review presents a comprehensive overview of all metrics and calculations used to determine the degree of tortuosity of retinal blood vessels.

In this article, we introduce a very low-price smartphone fundus camera device with basic amenities. It has become very fruitful toward undergraduate teaching at the bedside or in the outpatient department, especially where there are no facilities for the fundus camera unit. A fundus camera unit is an essential part of retina clinic, and it is very costly. Fundus photographs are very essential for disease diagnosis, its follow-up, and for disease monitoring. It cannot be carried to the camp side. Commercially, available fundus cameras are the alternative to this, but again very costly. Almost zero price this innovation helps the students to see the fundus pathologies with their own eyes and make them more clinically oriented. [ABSTRACT FROM AUTHOR]

Digital fundus imaging is being used in diagnosis, documentation, and sharing of many retinal diseases and hence forms an essential part of ophthalmology. The use of smartphones for the same has been ever increasing. There is a need for simpler devices to couple the 20D lens and smartphone so as to take fundus photographs which can help in fundus documentation. This article describes a simple inexpensive technique of preparing a smartphone fundus photography device (Trash To Treasure (T3) Retcam) from the used materials in the clinics within minutes. This article will also review the optical principles of the T3 Retcam and describe the step–by–step method to record good-quality retinal image/videos. This inexpensive device is made by recycling and modifying the plastic hand sanitizer bottle in the clinics/hospitals which can be used for documenting, diagnosing, screening, and academic purposes.

In this paper, the H-minima transform is used for blood vessel segmentation. The aim of this study is to get the high accuracy of blood vessel segmentation in retinal images. In this study the good result and good performance were got. We compared our result with other methods. Also for simulation result we implemented on DRIVE and STARE database. The proposed method shows very remarkable performance on pathological retinal images. For the implementing of the proposed method MATLAB 2019a software is used. The running time of this method was 1 s for each image and the average accuracy for STARE dataset and DRIVE dataset achieved to 0.9591 and 0.9672 respectively. [ABSTRACT FROM AUTHOR]

The eye, the photoreceptive organ used to perceive the external environment, is of great importance to humans. It has been proven that some diseases in humans are accompanied by fundus changes; therefore, the health status of people may be interpreted from retinal images. However, the human eye is not a perfect refractive system for the existence of ocular aberrations. These aberrations not only affect the ability of human visual discrimination and recognition, but restrict the observation of the fine structures of human eye and reduce the possibility of exploring the mechanisms of eye disease. Adaptive optics (AO) is a technique that corrects optical wavefront aberrations. Once integrated into ophthalmoscopes, AO enables retinal imaging at the cellular level. This paper illustrates the principle of AO in correcting wavefront aberrations in human eyes, and then reviews the applications and advances of AO in ophthalmology, including the adaptive optics fundus camera (AO-FC), the adaptive optics scanning laser ophthalmoscope (AO-SLO), the adaptive optics optical coherence tomography (AO-OCT), and their combined multimodal imaging technologies. The future development trend of AO in ophthalmology is also prospected.

Nowadays in ophthalmologic practice several commercial instruments are available to image patient retinas in vivo. Many modern fundus cameras and confocal scanning laser ophthalmoscopes allow acquisition of two dimensional en face images of the retina with both back reflected as well as fluorescent light. Additionally, optical coherence tomography systems allow non-invasive probing of three-dimensional retinal morphology. For all of these instruments the available lateral resolution is limited by optical quality of the human eye used as the imaging objective. To improve lateral resolution and achieve diffraction-limited imaging, adaptive optics (AO) can be implemented with any of these imaging systems to correct both static and dynamic aberrations inherent in human eyes. Most of the wavefront correctors used previously in AO systems have limited dynamic range and an insufficient number of actuators to achieve diffraction-limited correction of most human eyes. Thus, additional corrections were necessary, either by trial lenses or additional deformable mirrors (DMs). The UC Davis AO flood-illuminated fundus camera system described in this paper has been previously used to acquire in vivo images of the photoreceptor mosaic and for psychophysical studies on normal and diseased retinas. These results were acquired using a DM manufactured by Litton ITEK (DM109), which has 109 actuators arranged in a hexagonal array below a continuous front-surface mirror. It has an approximate surface actuator stroke of ±2μm. Here we present results with a new hi-speed magnetic DM manufactured by ALPAO (DM97, voice coil technology), which has 97 actuators and similar inter-actuator stroke (>3μm, mirror surface) but much higher low-order aberration correction (defocus stroke of at least ±30μm) than the previous one. In this paper we report results of testing performance of the ALPAO DM for the correction of human eye aberrations. Additionally changes made to our AO flood illuminated system are presented along with images of the model eye retina and in-vivo human retina acquired with this system. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Nowadays in ophthalmologic practice several commercial instruments are available to image patient retinas in vivo. Many modern fundus cameras and confocal scanning laser ophthalmoscopes allow acquisition of two dimensional en face images of the retina with both back reflected as well as fluorescent light. Additionally, optical coherence tomography systems allow non-invasive probing of three-dimensional retinal morphology. For all of these instruments the available lateral resolution is limited by optical quality of the human eye used as the imaging objective. To improve lateral resolution and achieve diffraction-limited imaging, adaptive optics (AO) can be implemented with any of these imaging systems to correct both static and dynamic aberrations inherent in human eyes. Most of the wavefront correctors used previously in AO systems have limited dynamic range and an insufficient number of actuators to achieve diffraction-limited correction of most human eyes. Thus, additional corrections were necessary, either by trial lenses or additional deformable mirrors (DMs). The UC Davis AO flood-illuminated fundus camera system described in this paper has been previously used to acquire in vivo images of the photoreceptor mosaic and for psychophysical studies on normal and diseased retinas. These results were acquired using a DM manufactured by Litton ITEK (DM109), which has 109 actuators arranged in a hexagonal array below a continuous front-surface mirror. It has an approximate surface actuator stroke of ±2μm. Here we present results with a new hi-speed magnetic DM manufactured by ALPAO (DM97, voice coil technology), which has 97 actuators and similar inter-actuator stroke (>3μm, mirror surface) but much higher low-order aberration correction (defocus stroke of at least ±30μm) than the previous one. In this paper we report results of testing performance of the ALPAO DM for the correction of human eye aberrations. Additionally changes made to our AO flood illuminated system are presented along with images of the model eye retina and in-vivo human retina acquired with this system. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Purpose: The aim is to evaluate the diagnostic accuracy of digital fundus photography in diabetic retinopathy (DR) screening at a single university hospital. Methods: This was a cross-sectional hospital-based study. One hundred and ninety-eight diabetic patients were recruited for comprehensive eye examination by two ophthalmologists. Five-field fundus photographs were taken with a digital, nonmydriatic fundus camera, and trained primary care physicians then graded the severity of DR present by single-field 45° and five-field fundus photography. Sensitivity and specificity of DR grading were reported using the findings from the ophthalmologists' examinations as a gold standard. Results: When fundus photographs of the participants' 363 eyes were analyzed for the presence of DR, there was substantial agreement between the two primary care physicians, κ = 0.6226 for single-field and 0.6939 for five-field photograph interpretation. The sensitivity and specificity of DR detection with single-field photographs were 70.7% (95% Confidence interval [CI]; 60.2%–79.7%) and 99.3% (95% CI; 97.4%–99.9%), respectively. Sensitivity and specificity for five-field photographs were 84.5% (95% CI; 75.8%–91.1%) and 98.6% (95% CI; 96.5%–99.6%), respectively. The receiver operating characteristic was 0.85 (0.80–0.90) for single-field photographs and 0.92 (0.88–0.95) for five-field photographs. Conclusion: The sensitivity and specificity of fundus photographs for DR detection by primary care physicians were acceptable. Single- and five-field digital fundus photography each represent a convenient screening tool with acceptable accuracy.

PURPOSE: To evaluate the use of non-mydriatic fundus camera as a screening modality for diabetic retinopathy in a sample of population in Riyadh, Saudi Arabia. METHODS: Patients coming, from April 2015 till September 2018, for their diabetic check up at the diabetic center clinics in King Abdul-Aziz University hospital were screened using a non-mydriatic fundus camera (NMFC). Photos were graded by retina specialist and compared to the findings of dilated fundus examination (DFE) by retina specialists. RESULTS: The grading results of NMFC and DFE were compared and the overall sensitivity and specificity for detection of diabetic retinopathy within one grade of retinopathy was 98.7% and 80% respectively. The sensitivity for detection of sight threatening conditions such as proliferative diabetic retinopathy, severe non-proliferative diabetic retinopathy, and diabetic macular edema (by Ocular Coherence Tomography) was found to be 86.7%, 90.3% and 100% respectively; while the specificity was found to be 96.5%, 93%, and 100% respectively. CONCLUSION: Non-mydriatic fundus camera has a high sensitivity and specificity in screening for diabetic retinopathy. It is a great screening tool, which is user friendly and can be operated by trained nurses in primary clinics during patient's regular routine diabetic checkups. It aids in early detection of sight threatening conditions which need urgent referral to ophthalmologists. [ABSTRACT FROM AUTHOR]

Emergency physicians (EPs) frequently evaluate patients at risk for sight-threatening conditions but may have difficulty performing direct ophthalmoscopy effectively. Digital fundus photography offers a potential alternative. We sought to assess the performance of an automated digital retinal imaging platform in a real-world emergency department. We performed a prospective, observational study of emergency department patients who were at risk for acute, nontraumatic, posterior segment pathology. Photographs were obtained using an automated digital retinal camera and were subsequently reviewed by an ophthalmologist. We recorded the number of attempts required, total time required, patient comfort, and findings on EP-performed direct ophthalmoscopy, if performed. Of 123 participants completing the study, 93 (75.6%) had ≥1 eye with a diagnostically useful image, while 29 (23.6%) had no photographs of diagnostic value. The mean number of attempts required to obtain images was 1.45 (range 1–3) and the mean elapsed time required to complete photography was 109.6 s. The mean patient comfort score was 4.6 on a 5-point scale, where 5 was the most comfortable. Direct ophthalmoscopy was performed by an emergency department provider for 19 (15.4%) patients. Acute findings were noted in 14 patients during expert review of fundus photographs, though in only 2 of these cases was direct ophthalmoscopy performed by an EP with only 1 finding ultimately identified correctly. Automated digital imaging of the ocular fundus is rapidly performed, is well tolerated by patients, and can be used to obtain diagnostic quality images without the use of pharmacologic pupillary dilation in most emergency department patients who are at risk for acute posterior segment pathology. [ABSTRACT FROM AUTHOR]

Objective: To study the accuracy and agreement of non-mydriatic fundus photographic screening of diabetic retinopathy (DR) by well-trained paramedic personnel compared to retinal specialists and to obtain the prevalence of DR stages in primary care unit (PCU). Methods: The non-mydriatic fundus photographs of diabetic patients taken at PCU were retrospectively reviewed and graded into three groups; no DR, non-proliferative DR (NPDR), proliferative DR (PDR) by two independent well-trained nurses compared to retinal specialists between November, 2015 to March, 2016. The results were statistically analyzed to determine the level of agreement between the nurses and the retinal specialists. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of each nurse were also calculated. Results: Fundus photographs of 475 patients were obtained. The patients included 129 (27.2%) males and 346 (72.8%) females with the age of 59.94 ± 8.62 years. The agreements between two readers and the retinal specialists were moderate (κ =0.46 and 0.54). The sensitivity and specificity of the first reader were 71.69% and 87.91% and the second reader were 75.50% and 90.8%, respectively. The PPV and NPV were 42.69% and 98.11% for the first reader and 50.60% and 96.70% for the second. The overall accuracy of the first nurse was 86.1% while the second was 96.0%. The prevalence of any stages of DR was 11.1%, NPDR 10.5% and PDR 0.6%. Conclusion: The single field non-mydriatic fundus photography read by trained paramedic personnel is one of the effective preliminary screening modalities. However, the continuous evaluation of the capabilities of the readers should be performed so that the patients with any stages of DR would be appropriately referred to ophthalmologists. This strategy would lead to the significant improvement of the DR screening in the country with high burden of diabetic patients.

Our study aimed to assess the role of a hand-held fundus camera and artificial intelligence (AI)-based grading system in diabetic retinopathy (DR) screening and determine its diagnostic accuracy in detecting DR compared with clinical examination and a standard fundus camera. This cross-sectional instrument validation study, as a part of the International Diabetes Federation (IDF) Diabetic Retinopathy Screening Project, included 160 patients (320 eyes) with type 2 diabetes (T2DM). After the standard indirect slit-lamp fundoscopy, each patient first underwent fundus photography with a standard 45° camera VISUCAM Zeiss and then with a hand-held camera TANG (Shanghai Zhi Tang Health Technology Co., Ltd.). Two retina specialists independently graded the images taken with the standard camera, while the images taken with the hand-held camera were graded using the DeepDR system and an independent IDF ophthalmologist. The three screening methods did not differ in detecting moderate/severe nonproliferative and proliferative DR. The area under the curve, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, kappa (ĸ) agreement, diagnostic odds ratio, and diagnostic effectiveness for a hand-held camera compared to clinical examination were 0.921, 89.1%, 100%, 100%, 91.4%, infinity, 0.11, 0.86, 936.48, and 94.9%, while compared to the standard fundus camera were 0.883, 83.2%, 100%, 100%, 87.3%, infinity, 0.17, 0.78, 574.6, and 92.2%. The results of our study suggest that fundus photography with a hand-held camera and AI-based grading system is a short, simple, and accurate method for the screening and early detection of DR, comparable to clinical examination and fundus photography with a standard camera.

We present a multispectral fundus camera that performs fast imaging of the ocular posterior pole in the visible and near-infrared (400 to 1300 nm) wavelengths through 15 spectral bands, using a flashlight source made of light-emitting diodes, and CMOS and InGaAs cameras. We investigate the potential of this system for visualizing occult and overlapping structures of the retina in the unexplored wavelength range beyond 900 nm, in which radiation can penetrate deeper into the tissue. Reflectance values at each pixel are also retrieved from the acquired images in the analyzed spectral range. The available spectroscopic information and the visualization of retinal structures, specifically the choroidal vasculature and drusen-induced retinal pigment epithelium degeneration, which are hardly visible in conventional color fundus images, underline the clinical potential of this system as a new tool for ophthalmic diagnosis. [ABSTRACT FROM AUTHOR]

Digital fundus imaging is being used in diagnosis, documentation, and sharing of many retinal diseases and hence forms an essential part of ophthalmology. The use of smartphones for the same has been ever increasing. There is a need for simpler devices to couple the 20D lens and smartphone so as to take fundus photographs which can help in fundus documentation. This article describes a simple inexpensive technique of preparing a smartphone fundus photography device (Trash To Treasure (T3) Retcam) from the used materials in the clinics within minutes. This article will also review the optical principles of the T3 Retcam and describe the step-by-step method to record good-quality retinal image/videos. This inexpensive device is made by recycling and modifying the plastic hand sanitizer bottle in the clinics/hospitals which can be used for documenting, diagnosing, screening, and academic purposes. [ABSTRACT FROM AUTHOR]

This article describes the method to make a do it yourself smartphone-based fundus camera which can image the central retina as well as the peripheral retina up to the pars plana. It is a cost-effective alternative to the fundus camera.

The aim of this study is to describe the application of teleophthalmology in screening for diabetic retinopathy in association with diabetes centers. Our model of diabetic retinopathy screening uses, technology innovation to reach out to patients who would otherwise not visit eye hospitals regularly. With more than 70 million diabetic population and only 20,000 ophthalmologists, a regular model of patients visiting eye care practitioners in person is not a feasible option in India. Technology can be used to address this gap, wherein Welcare sets up a telemedicine facility in existing diabetes centers, which includes a fundus camera, telemedicine platform and also more importantly provides a network of reporting ophthalmologists who see the images from these centers and report back within ½ h. Teleophthalmology can be a very effective model for screening of diabetic retinopathy and can help in greater detection of retinopathy and can help prevent a large number of patients from irreversible vision loss.