scholarly journals Automatic Screening and Grading of Age-Related Macular Degeneration from Texture Analysis of Fundus Images

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Thanh Vân Phan ◽  
Lama Seoud ◽  
Hadi Chakor ◽  
Farida Cheriet
Keyword(s):  
Support Vector Machine ◽  
Random Forest ◽  
Macular Degeneration ◽  
The Elderly ◽  
Local Binary Patterns ◽  
Age Related Macular Degeneration ◽  
Support Vector ◽  
Visual Context ◽  
Fundus Images ◽  
Age Related

Age-related macular degeneration (AMD) is a disease which causes visual deficiency and irreversible blindness to the elderly. In this paper, an automatic classification method for AMD is proposed to perform robust and reproducible assessments in a telemedicine context. First, a study was carried out to highlight the most relevant features for AMD characterization based on texture, color, and visual context in fundus images. A support vector machine and a random forest were used to classify images according to the different AMD stages following the AREDS protocol and to evaluate the features’ relevance. Experiments were conducted on a database of 279 fundus images coming from a telemedicine platform. The results demonstrate that local binary patterns in multiresolution are the most relevant for AMD classification, regardless of the classifier used. Depending on the classification task, our method achieves promising performances with areas under the ROC curve between 0.739 and 0.874 for screening and between 0.469 and 0.685 for grading. Moreover, the proposed automatic AMD classification system is robust with respect to image quality.

scholarly journals Computer-Aided Age-Related Macular Degeneration Diagnosis with the Fusion of Both Color Fundus and Fluorescein Angiography

2020 ◽  
Author(s):  
Zekuan Yu ◽  
Jianchen Hao ◽  
Zifeng Tian ◽  
Bin Qiu ◽  
Shujin Zhu ◽  
...  
Keyword(s):  
Macular Degeneration ◽  
Fluorescein Angiography ◽  
Age Related Macular Degeneration ◽  
Quadratic Functions ◽  
Support Vector ◽  
Fundus Images ◽  
Cad System ◽  
Age Related ◽  
Computer Aided ◽  
Color Fundus Images

Abstract Background: Age-related macular degeneration (AMD) is one of the most severe vision-threatening diseases, and yet Fundus Fluorescein Angiography (FFA) is the gold standard for AMD diagnosis. In recent years, many AMD computer-aided diagnosis (CAD) systems have been developed based on either color fundus images or OCT images. However, there is no CAD technique that integrates FFA with other ophthalmic imaging so far. Methods: In order to improve the performance of AMD CAD system, we propose a pioneering CAD pipeline that combines color fundus and FFA photography. This novel pipeline is the first work that incorporates FFA with any other modality. Six deep neural networks (ResNet-18, ResNet-50, ResNet-101, Inception-V3, Inception-ResNetV2, and DenseNet-201) were utilized to extract feature vectors to facilitate five classifiers (Random Forest, K-Nearest Neighbor, and Support Vector Machine with Linear, Gaussian, and Quadratic functions) for AMD diagnosis. The pipeline was validated on 664 pairs of color fundus and FFA images using 10-fold cross-validation. Results and conclusion: The accuracy and area under curve (AUC) value achieves 93.8% and 0.97, respectively. The results demonstrate that combining color fundus images and FFA images in CAD system is beneficial for AMD diagnosis, indicating promising potential to clinical practice in the future.

scholarly journals Impact of neovascular age-related macular degeneration: burden of patients receiving therapies in Japan

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shigeru Honda ◽  
Yasuo Yanagi ◽  
Hideki Koizumi ◽  
Yirong Chen ◽  
Satoru Tanaka ◽  
...  
Keyword(s):  
Macular Degeneration ◽  
Productivity Loss ◽  
Work Productivity ◽  
The Elderly ◽  
Developed Countries ◽  
Age Related Macular Degeneration ◽  
Resource Utilisation ◽  
Total Work ◽  
Healthcare Resource Utilisation ◽  
Age Related

AbstractThe chronic eye disorder, neovascular age-related macular degeneration (nAMD), is a common cause of permanent vision impairment and blindness among the elderly in developed countries, including Japan. This study aimed to investigate the disease burden of nAMD patients under treatment, using data from the Japan National Health and Wellness surveys 2009–2014. Out of 147,272 respondents, 100 nAMD patients reported currently receiving treatment. Controls without nAMD were selected by 1:4 propensity score matching. Healthcare Resource Utilisation (HRU), Health-Related Quality of Life (HRQoL), and work productivity loss were compared between the groups. Regarding HRU, nAMD patients had significantly increased number of visits to any healthcare provider (HCP) (13.8 vs. 8.2), ophthalmologist (5.6 vs. 0.8), and other HCP (9.5 vs. 7.1) compared to controls after adjusting for confounding factors. Additionally, nAMD patients had reduced HRQoL and work productivity, i.e., reduced physical component summary (PCS) score (46.3 vs. 47.9), increased absenteeism (18.14% vs. 0.24%), presenteeism (23.89% vs. 12.44%), and total work productivity impairment (33.57% vs. 16.24%). The increased number of ophthalmologist visits were associated with decreased PCS score, increased presenteeism and total work productivity impairment. The current study highlighted substantial burden for nAMD patients, requiring further attention for future healthcare planning and treatment development.

scholarly journals Neovascular Macular Degeneration: A Review of Etiology, Risk Factors, and Recent Advances in Research and Therapy

2021 ◽  
Vol 22 (3) ◽  
pp. 1170
Author(s):  
Arunbalaji Pugazhendhi ◽  
Margaret Hubbell ◽  
Pooja Jairam ◽  
Balamurali Ambati
Keyword(s):  
Risk Factors ◽  
Macular Degeneration ◽  
Kinase Inhibitors ◽  
Rho Kinase ◽  
The Elderly ◽  
Age Related Macular Degeneration ◽  
Gene Therapies ◽  
Rho Kinase Inhibitors ◽  
Age Related ◽  
Endothelial Growth Factor

Neovascular age-related macular degeneration (exudative or wet AMD) is a prevalent, progressive retinal degenerative macular disease that is characterized by neovascularization of the choroid, mainly affecting the elderly population causing gradual vision impairment. Risk factors such as age, race, genetics, iris color, smoking, drinking, BMI, and diet all play a part in nvAMD’s progression, with anti-vascular endothelial growth factor (anti-VEGF) therapy being the mainstay of treatment. Current therapeutic advancements slow the progression of the disease but do not cure or reverse its course. Newer therapies such as gene therapies, Rho-kinase inhibitors, and levodopa offer potential new targets for treatment.

scholarly journals Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

2014 ◽  
Vol 53 ◽  
pp. 55-64 ◽  
Author(s):  
Muthu Rama Krishnan Mookiah ◽  
U. Rajendra Acharya ◽  
Joel E.W. Koh ◽  
Vinod Chandran ◽  
Chua Kuang Chua ◽  
...  
Keyword(s):  
Macular Degeneration ◽  
Age Related Macular Degeneration ◽  
Fundus Images ◽  
Automated Diagnosis ◽  
Age Related

scholarly journals Introduction to the multi-author review on macular degeneration

2020 ◽  
Vol 77 (5) ◽  
pp. 779-780 ◽  
Author(s):  
Anu Kauppinen
Keyword(s):  
Macular Degeneration ◽  
Vision Loss ◽  
The Elderly ◽  
Developed Countries ◽  
Age Related Macular Degeneration ◽  
Age Related ◽  
Severe Vision Loss ◽  
Author Review ◽  
Dry Amd ◽  
Endothelial Growth Factor

AbstractProlonged life expectancies contribute to the increasing prevalence of age-related macular degeneration (AMD) that is already the leading cause of severe vision loss among the elderly in developed countries. In dry AMD, the disease culminates into vast retinal atrophy, whereas the wet form is characterized by retinal edema and sudden vision loss due to neovascularization originating from the choroid beneath the Bruch’s membrane. There is no treatment for dry AMD and despite intravitreal injections of anti-vascular endothelial growth factor (VEGF) that suppress the neovessel formation, also wet AMD needs new therapies to prevent the disease progression and to serve patients lacking of positive response to current medicines. Knowledge on disease mechanisms is a prerequisite for the drug development, which is hindered by the multifactorial nature of AMD. Numerous distinguished publications have revealed AMD mechanisms at the cellular and molecular level and in this multi-author review, we take a bit broader look at the topic with some novel aspects.

AN AUTOMATED METHOD TO DETECT AGE-RELATED MACULAR DEGENERATION FROM OPTICAL COHERENCE TOMOGRAPHIC IMAGES

2021 ◽  
pp. 2150036
Author(s):  
Anju Thomas ◽  
P. M. Harikrishnan ◽  
Varun P. Gopi ◽  
P. Palanisamy
Keyword(s):  
Early Detection ◽  
Macular Degeneration ◽  
The Elderly ◽  
Age Related Macular Degeneration ◽  
Data Sets ◽  
Sigmoid Function ◽  
Data Set ◽  
Automated Method ◽  
Age Related ◽  
Sd Oct

Age-related macular degeneration (AMD) is an eye disease that affects the elderly. AMD’s prevalence is increasing as society’s population ages; thus, early detection is critical to prevent vision loss in the elderly. Arrangement of a comprehensive examination of the eye for AMD detection is a challenging task. This paper suggests a new poly scale and dual path (PSDP) convolutional neural network (CNN) architecture for early-stage AMD diagnosis automatically. The proposed PSDP architecture has nine convolutional layers to classify the input image as AMD or normal. A PSDP architecture is used to enhance classification efficiency due to the high variation in size and shape of perforation present in OCT images. The poly scale approach employs filters of various sizes to extract features from local regions more effectively. Simultaneously, the dual path architecture incorporates features extracted from different CNN layers to boost features in the global regions. The sigmoid function is used to classify images into binary categories. The Mendeley data set is used to train the proposed network and tested on Mendeley, Duke, SD-OCT Noor, and OCTID data sets. The testing accuracy of the network in Mendeley, Duke, SD-OCT Noor, and OCT-ID is 99.73%,96.66%,94.89%,99.61%, respectively. The comparison with alternative approaches showed that the proposed algorithm is efficient in detecting AMD. Despite having been trained on the Mendeley data set, the proposed model exhibited good detection accuracy when tested on other data sets. This shows that the suggested model can distinguish AMD/Normal images from various data sets. As compared to other methods, the findings show that the proposed algorithm is efficient at detecting AMD. Rapid eye scanning for early detection of AMD could be possible with the proposed architecture. The proposed CNN can be applied in real-time due to its lower complexity and less learnable parameters.

Epidemiology Prevalence and Incidence in Dry-Form (Non-Neovascular) Age-Related Macular Degeneration

2017 ◽  
pp. 97-99
Keyword(s):  
Macular Degeneration ◽  
Elderly Population ◽  
The Elderly ◽  
Epidemiologic Studies ◽  
Age Related Macular Degeneration ◽  
Neovascular Amd ◽  
Age Related ◽  
Dry Amd ◽  
Degenerative Disorder ◽  
Definition Of

Age-related macular degeneration (AMD) is a degenerative disorder of the central retina and represents the leading cause of severe visual impairment in the elderly population of industrialized societies. It is known that it currently exists between 30 and 50 million people around the world and is estimated that will have doubled by the end of the coming decade. Several large epidemiologic studies have evaluated the prevalence of non-neovascular or so-called dry AMD. There is some variation in the prevalence of non-neovascular AMD depending on the exact definition of AMD. All of them report a higher prevalence of early AMD and an increasing prevalence with age. It is seen most in Caucasians and least in people with Africans and it is not related to gender.

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