A Smartphone-Based Tool for Rapid, Portable, and Automated Wide-Field Retinal Imaging.

Purpose:High-quality, wide-field retinal imaging is a valuable method for screening preventable, vision-threatening diseases of the retina. Smartphone-based retinal cameras hold promise for increasing access to retinal imaging, but variable image quality and restricted field of view can limit their utility. We developed and clinically tested a smartphone-based system that addresses these challenges with automation-assisted imaging. Methods:The system was designed to improve smartphone retinal imaging by combining automated fixation guidance, photomontage, and multicolored illumination with optimized optics, user-tested ergonomics, and touch-screen interface. System performance was evaluated from images of ophthalmic patients taken by nonophthalmic personnel. Two masked ophthalmologists evaluated images for abnormalities and disease severity. Results:The system automatically generated 100° retinal photomontages from five overlapping images in under 1 minute at full resolution (52.3 pixels per retinal degree) fully on-phone, revealing numerous retinal abnormalities. Feasibility of the system for diabetic retinopathy (DR) screening using the retinal photomontages was performed in 71 diabetics by masked graders. DR grade matched perfectly with dilated clinical examination in 55.1% of eyes and within 1 severity level for 85.2% of eyes. For referral-warranted DR, average sensitivity was 93.3% and specificity 56.8%. Conclusions:Automation-assisted imaging produced high-quality, wide-field retinal images that demonstrate the potential of smartphone-based retinal cameras to be used for retinal disease screening. Translational Relevance:Enhancement of smartphone-based retinal imaging through automation and software intelligence holds great promise for increasing the accessibility of retinal screening

Smartphone-based, rapid, wide-field fundus photography for diagnosis of pediatric retinal diseases

PurposeAn important, unmet clinical need is for cost-effective, reliable, easy-to-use, and portable retinal photography to evaluate preventable causes of vision loss in children. This study presents the feasibility of a novel smartphone-based retinal imaging device tailored to imaging the pediatric fundus.MethodsSeveral modifications for children were made to our previous device, including a child-friendly 3D printed housing of animals, attention-grabbing targets, enhanced image stitching, and video-recording capabilities. Retinal photographs were obtained in children undergoing routine dilated eye examination. Experienced masked retina-specialist graders determined photograph quality and made diagnoses based on the images, which were compared to the treating clinician's diagnosis.ResultsDilated fundus photographs were acquired in 43 patients with a mean age of 6.7 years. The diagnoses included retinoblastoma, Coats' disease, commotio retinae, and optic nerve hypoplasia, among others. Mean time to acquire five standard photographs totaling 90-degree field of vision was 2.3 ± 1.1 minutes. Patients rated their experience of image acquisition favorably, with a Likert score of 4.6 ± 0.8 out of 5. There was 96% agreement between image-based diagnosis and the treating clinician's diagnosis.ConclusionsWe report a handheld smartphone-based device with modifications tailored for wide-field fundus photography in pediatric patients that can rapidly acquire fundus photos while being well-tolerated.Translational relevanceAdvances in handheld smartphone-based fundus photography devices decrease the technical barrier for image acquisition in children and may potentially increase access to ophthalmic care in communities with limited resources

Digital ocular fundus imaging: a review

Ocular fundus imaging plays a key role in monitoring the health status of the human eye. Currently, a large number of imaging modalities allow the assessment and/or quantification of ocular changes from a healthy status. This review focuses on the main digital fundus imaging modality, color fundus photography, with a brief overview of complementary techniques, such as fluorescein angiography. While focusing on two-dimensional color fundus photography, the authors address the evolution from nondigital to digital imaging and its impact on diagnosis. They also compare several studies performed along the transitional path of this technology. Retinal image processing and analysis, automated disease detection and identification of the stage of diabetic retinopathy (DR) are addressed as well. The authors emphasize the problems of image segmentation, focusing on the major landmark structures of the ocular fundus: the vascular network, optic disk and the fovea. Several proposed approaches for the automatic detection of signs of disease onset and progression, such as microaneurysms, are surveyed. A thorough comparison is conducted among different studies with regard to the number of eyes/subjects, imaging modality, fundus camera used, field of view and image resolution to identify the large variation in characteristics from one study to another. Similarly, the main features of the proposed classifications and algorithms for the automatic detection of DR are compared, thereby addressing computer-aided diagnosis and computer-aided detection for use in screening programs.Fundação para a Ciência e TecnologiaFEDErPrograma COMPET

Retinal image analysis: Image processing and feature extraction oriented to the clinical task

Medical digital imaging has become a key element of modern health care procedures. It provides visual documentation and a permanent record for the patients, and most important the ability to extract quantitative information about many diseases. Modern ophthalmology relies on the advances in digital imaging and computing power. In this paper we present an overview of the results from the doctoral dissertation by Andrés G. Marrugo. This dissertation contributes to the digital analysis of retinal images and the problems that arise along the imaging pipeline of fundus photography, a field that is commonly referred to as retinal image analysis. We have dealt with and proposed solutions to problems that arise in retinal image acquisition and longitudinal monitoring of retinal disease evolution. Specifically, non-uniform illumination compensation, poor image quality, automated focusing, image segmentation, change detection, space-invariant (SI) and space-variant (SV) blind deconvolution (BD). Digital retinal image analysis can be effective and cost-efficient for disease management, computeraided diagnosis, screening and telemedicine and applicable to a variety of disorders such as glaucoma, macular degeneration, and retinopathy. © 2017. Sociedad Española de Óptica. All right reserved

Deep Learning Methods for Diabetic Eye Disease Screening and Smartphone-based Applications

Vision is an essential part of daily life, for many this can be disrupted by several diseases like diabetes and cause severe eye complications or even blindness. With frequent eye screening early detection and prevention of blindness can be possible, however, there is still a global discrepancy in the availability and accessibility of eye care. In this Master’s Thesis, the possibility of providing affordable and efficient automatic diabetic eye disease screening using low-cost lenses, smartphones, and AI methods with the current technology is investigated and applications in the medical practice are discussed. A comprehensive review was performed to analyze the current state of the art AI methods. A market review about the products related to mobile ophthalmology was conveyed for affordability analysis. As part of the collaborative work, a systematic review was also conducted on AI applications for Inherited Retinal Disorders. On the other hand, testing was carried out to assess the efficiency of the chosen AI methods and both the dataset and base architecture impact on the AI algorithm were assessed by statistical analysis methods. Results suggest that multi-disease approaches perform slightly better than disease-specific ones where DR detection has higher values, and EfficientNet architectures achieve higher accuracy scores. All in all, using DL algorithms, automatic diabetic eye disease screening in mobile settings is achievable in the medical practice and can have huge impacts in the rural areas and less developed regions around the world.A visão é uma parte fundamental da vida diária. Para muitas pessoas, pode ser perturbada por várias doenças como a diabetes, levando a complicações oculares graves ou mesmo à cegueira. Através de rastreios oculares frequentes, a detecção precoce e a prevenção da cegueira podem ser possíveis, mas ainda existe uma discrepância global na disponibilidade e acessibilidade a cuidados médicos para a visão. Nesta tese de mestrado, a possibilidade de rastreio automatizado acessível e eficiente de doenças oculares diabéticas usando lentes ópticas de baixo custo, smartphones, e métodos de IA, é explorada com o estado actual da investigação, e as potenciais aplicações na prática médica são discutidas. Foi realizada uma pesquisa exaustiva para analisar o estado actual dos métodos de IA. Foi também realizado um estudo de mercado de produtos no campo da oftalmologia móvel para analisar a acessibilidade de preços. Como parte do trabalho de colaboração, foi também realizada uma revisão sistemática das aplicações de IA para doenças hereditárias da retina. Por outro lado, foram realizados testes para avaliar a eficiência dos métodos de IA escolhidos, e tanto o conjunto de dados como a arquitectura de base foram examinados quanto à sua influência no algoritmo da IA utilizando métodos de análise estatística. Os resultados sugerem que os métodos multi-doenças, que consideram múltiplas doenças, têm um desempenho ligeiramente melhor do que os métodos específicos de doenças, onde a detecção de DR tem valores mais elevados, e que as arquitecturas EfficientNet obtêm resultados de maior precisão. Em geral, utilizando algoritmos DL, o rastreio automatizado para doenças oculares diabéticas em ambientes móveis é viável na prática médica e pode ter grande impacto em áreas rurais e regiões menos desenvolvidas em todo o mundo

Quality changes in fundus images of pseudophakic eyes

We consider the changes produced in the quality of eye fundus images of patients before and after cataract surgery with intraocular lens implantation and propose a measure to quantitatively assess those changes. Several factors concerning the optical system of the eye, the ocular media, and the specific characteristics of the implanted intraocular lens, may influence the quality of the digital image acquired with a non-mydriatic retinal camera. We illustrate our study with several cases taken from the clinical practice. A pair of pre- and post-operative eye fundus images represents each case. To measure image quality, we carry out a calculation of image anisotropy on each image. The results show that after surgery with intraocular lens implant, a fundus image is usually much brighter, sharp and higher quality. However, this rule of thumb can be altered by several conditions. For example, the multifocal design of the intraocular implant after a clear lens extraction. The anisotropy-based measure has revealed to be a suitable tool to quantitatively assess quality changes between pre-and post-operative fundus images. © Sociedad Española de Óptica.En este trabajo estudiamos los cambios producidos en la calidad de imágenes del fondo de ojo de pacientes antes y después de cirugía de catarata con implantación de lente intraocular, y proponemos una medida para evaluar esos cambios cuantitativamente. Diversos factores relacionados con el sistema óptico del ojo, los medios oculares y las características específicas de la lente intraocular implantada pueden influir en la calidad de la imagen digital adquirida con una cámara de retina no midriática. Ilustramos el estudio con varios casos tomados de la práctica clínica. Un par de imágenes del fondo de ojo pre y post-operatorias representa cada caso. Para medir la calidad de la imagen, llevamos a cabo un cálculo de la anisotropía en cada imagen. Los resultados muestran que después de la cirugía con implante de lente intraocular, una imagen de fondo de ojo suele ser mucho más brillante, nítida y de mayor calidad. Sin embargo, esta regla práctica puede verse alterada por varias condiciones. Por ejemplo, el diseño multifocal del implante intraocular después de una extracción de cristalino transparente. La medida basada en la anisotropía demostró ser una herramienta adecuada para evaluar cuantitativamente los cambios de calidad entre las imágenes del fondo de ojo pre y postoperatorias. © Sociedad Española de Óptica.Federación Española de Enfermedades Raras, FEDER, Ministerio de Economía y Competitividad, MINEC

Optical Design of a Retinal Image Acquisition Device for Mobile Diabetic Retinopathy Assessment

Diabetes mellitus is a condition that lead to various systemic alterations. These changes, taking place in the blood vessels cause a progressive capillary occlusion and, in the posterior eye region, provoke leakages from the vessels to the retina leading to a disease called diabetic retinopathy. This pathology ultimately can lead to complete vision loss, which is an aspect that emphasizes the relevance of the work developed in this thesis. The initial progression is asymptomatic, so only in advanced and frequently irreversible stages, the patient becomes aware of the disease. For this reason, a regular follow-up accomplished by eye fundus examination should be performed. Even though, for logistic motivations (lack of equipment, absence of ophthalmology specialists...) the progression-study and diagnose of the disease is often neglected. To encourage high coverage screening, a compact optical system was designed for a handheld and smartphone-based fundus camera prototype. The key features for the optical system are the low-cost achieved through a simple lens system and a mobile and non-mydriatic acquisition of fundus images with high field-of-view, by a smartphone camera. The simplicity of the optical system was accomplished by a three lens system setup. The results reveal a system with only a few aberrations in the periphery but with a good resolution at the center of a 41° field-of-view. Besides the optical system, a mechanical prototype was designed with the purpose of being 3D printed and easily portable. Also, a light hazard testing procedure was established and applied on a previously developed prototype. In the future, the implementation of the optical system in the prototype is intended, in order to confirm the applicability of the design in diminishing the burden of screening actions and consequently, empower the early treatment of the pathology