scholarly journals Entropy Rate Superpixel Classification for Automatic Red Lesion Detection in Fundus Images

Entropy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 417 ◽  
Author(s):  
Roberto Romero-Oraá ◽  
Jorge Jiménez-García ◽  
María García ◽  
María I. López-Gálvez ◽  
Javier Oraá-Pérez ◽  
...  
Keyword(s):  
Large Scale ◽  
Developed Countries ◽  
Lesion Detection ◽  
Entropy Rate ◽  
Diabetic Patients ◽  
Fundus Images ◽  
Test Set ◽  
Image Appearance ◽  
Working Age ◽  
Color Fundus Images

Diabetic retinopathy (DR) is the main cause of blindness in the working-age population in developed countries. Digital color fundus images can be analyzed to detect lesions for large-scale screening. Thereby, automated systems can be helpful in the diagnosis of this disease. The aim of this study was to develop a method to automatically detect red lesions (RLs) in retinal images, including hemorrhages and microaneurysms. These signs are the earliest indicators of DR. Firstly, we performed a novel preprocessing stage to normalize the inter-image and intra-image appearance and enhance the retinal structures. Secondly, the Entropy Rate Superpixel method was used to segment the potential RL candidates. Then, we reduced superpixel candidates by combining inaccurately fragmented regions within structures. Finally, we classified the superpixels using a multilayer perceptron neural network. The used database contained 564 fundus images. The DB was randomly divided into a training set and a test set. Results on the test set were measured using two different criteria. With a pixel-based criterion, we obtained a sensitivity of 81.43% and a positive predictive value of 86.59%. Using an image-based criterion, we reached 84.04% sensitivity, 85.00% specificity and 84.45% accuracy. The algorithm was also evaluated on the DiaretDB1 database. The proposed method could help specialists in the detection of RLs in diabetic patients.

scholarly journals Bright Lesion Detection in Color Fundus Images Based on Texture Features

2016 ◽  
Vol 12 (3) ◽  
pp. 355-360
Author(s):  
V. Ratna Bhargavi ◽  
Ranjan K. Senapati ◽  
Ganesh Methra ◽  
Sujitha Kandanulu
Keyword(s):  
Texture Features ◽  
Lesion Detection ◽  
Fundus Images ◽  
Color Fundus Images

NEW SEGMENTATION METHODOLOGY FOR EXUDATE DETECTION IN COLOR FUNDUS IMAGES

2013 ◽  
Vol 13 (01) ◽  
pp. 1350014 ◽  
Author(s):  
A. FEROUI ◽  
M. MESSADI ◽  
I. HADJIDJ ◽  
A. BESSAID
Keyword(s):  
Macular Edema ◽  
Mathematical Morphology ◽  
Clustering Algorithm ◽  
High Sensitivity ◽  
Diabetic Patients ◽  
Fundus Images ◽  
Manual Segmentation ◽  
Hard Exudates ◽  
Color Fundus Images ◽  
Good Detection

In this work, we developed an approach based on mathematical morphology and the k-means clustering algorithm to detect hard exudates (HEs) in images taken by retinography from different diabetic patients. The presence of exudates within the macular region is a hallmark of diabetic macular edema and is detected by diagnostics with high sensitivity. In ophthalmologic images, the segmentation of HEs is essential to characterize the shape of the lesion for analysis. In this domain, several approaches have been employed for exudate extraction. Some authors have used only the mathematical morphology, but this approach does not provide very good detection of exudates. In this paper, we combined the k-means clustering algorithm and the mathematical morphology. This approach was tested on a set of 50 ophthalmologic images. The obtained results were compared with manual segmentation by an ophthalmologist.

scholarly journals Levels of Inflammatory Cytokines IL-1β, IL-6, IL-8, IL-17A, and TNF-α in Aqueous Humour of Patients with Diabetic Retinopathy

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Songfu Feng ◽  
Honghua Yu ◽  
Ying Yu ◽  
Yu Geng ◽  
Dongli Li ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Inflammatory Cytokines ◽  
Aqueous Humour ◽  
Developed Countries ◽  
Diabetic Patients ◽  
Tnf Α ◽  
Cytokine Levels ◽  
Working Age ◽  
Retinal Complications

Diabetic retinopathy is the leading cause of blindness in working age individuals in developed countries. However, the role of inflammation in the pathogenesis of DR is not completely understood. This is an observational clinical research enrolling 80 type II diabetic patients who had undergone cataract surgeries either with DR or without DR. All cases were further categorized by the proliferative stages of retinal neovascularization and by the lengths of diabetic history. The levels of inflammatory cytokines including IL-1β, IL-6, IL-8, IL-17, and TNF-α in aqueous humour were tested. Results in this study indicated that these cytokine levels were increased in DR patients and might have a synergistic effect on the pathogenesis of this disease. They were also elevated along with the progression of neovascularization, reflecting the severity of DR. The results also suggested that for diabetic patients, the higher these levels are, the sooner retinal complications might appear. In conclusion, the levels of inflammatory cytokines IL-1β, IL-6, IL-8, IL-17A, and TNF-α in aqueous humour may be associated with the pathogenesis, severity, and prognosis of DR.

scholarly journals Diabetic Retinopathy Detection Using Walter-Klein Contrast Enhancement

2018 ◽  
Vol 2 (3) ◽  
Keyword(s):  
Diabetic Retinopathy ◽  
Developed Countries ◽  
Lesion Detection ◽  
Eye Disease ◽  
Retinal Images ◽  
Diabetic Patients ◽  
Multiple Classifiers ◽  
Retinal Lesion ◽  
The Developed Countries ◽  
Screening Systems

When sugar level (glucose) in the blood fails to regulate the insulin properly in human body, diabetic is occurred. The effect of diabetic on eye causes diabetic retinopathy. Diabetic retinopathy (DR) is a serious eye disease that originates from diabetes mellitus and is the most common cause of blindness in the developed countries. Therefore, much effort has been made to establish reliable computer aided screening systems based on color fund us images. Diabetic Retinopathy is one of a complicated diabetes which can cause blindness. It is a metabolic disordered patients perceive no symptoms until the disease is at late stage. So early detection and proper treatment has to be ensured. To serve this purpose, various automated systems have been designed. We propose an ensemble-based framework for retinal lesion detection. Unlike the well-known approach of considering the output of multiple classifiers, we propose a combination of of Retinal Lesion detectors, namely preprocessing methods and candidate extractors. The presence of micro aneurysms in the eye is one of the early signs of diabetic retinopathy. We analzye the input retinal images of the Diabetic patients and we can classify that the patient is affected by DR or not. If not affected, they are normal patient. If they are affected, further it classifies the different stages of diabetic retinopathy affected patients such as Mild, Moderate and Severe.

scholarly journals Validation of an Automated Screening System for Diabetic Retinopathy Operating under Real Clinical Conditions

2021 ◽  
Vol 11 (1) ◽  
pp. 14
Author(s):  
Soledad Jimenez-Carmona ◽  
Pedro Alemany-Marquez ◽  
Pablo Alvarez-Ramos ◽  
Eduardo Mayoral ◽  
Manuel Aguilar-Diosdado
Keyword(s):  
Diabetic Retinopathy ◽  
Large Scale ◽  
Developed Countries ◽  
Population Based ◽  
Diabetic Patients ◽  
Screening System ◽  
K Value ◽  
Aged People ◽  
Automated Screening ◽  
Clinical Conditions

Background: Retinopathy is the most common microvascular complication of diabetes mellitus. It is the leading cause of blindness among working-aged people in developed countries. The use of telemedicine in the screening system has enabled the application of large-scale population-based programs for early retinopathy detection in diabetic patients. However, the need to support ophthalmologists with other trained personnel remains a barrier to broadening its implementation. Methods: Automatic diagnosis of diabetic retinopathy was carried out through the analysis of retinal photographs using the 2iRetinex software. We compared the categorical diagnoses of absence/presence of retinopathy issued by family physicians (PCP) with the same categories provided by the algorithm (ALG). The agreed diagnosis of three specialist ophthalmologists is used as the reference standard (OPH). Results. There were 653 of 3520 patients diagnosed with diabetic retinopathy (DR). Diabetic retinopathy threatening to vision (STDR) was found in 82 patients (2.3%). Diagnostic sensitivity for STDR was 94% (ALG) and 95% (PCP). No patient with proliferating or severe DR was misdiagnosed in both strategies. The k-value of the agreement between the ALG and OPH was 0.5462, while between PCP and OPH was 0.5251 (p = 0.4291). Conclusions: The diagnostic capacity of 2iRetinex operating under normal clinical conditions is comparable to screening physicians.

scholarly journals Multi-label classification of fundus images based on graph convolutional network

2021 ◽  
Vol 21 (S2) ◽  
Author(s):  
Yinlin Cheng ◽  
Mengnan Ma ◽  
Xingyu Li ◽  
Yi Zhou
Keyword(s):  
Large Scale ◽  
Fundus Images ◽  
Convolutional Network ◽  
Hard Exudates ◽  
Proposed Model ◽  
Diabetic Population ◽  
Color Fundus Images ◽  
Aided Diagnosis ◽  
Large Scale Screening

Abstract Background Diabetic Retinopathy (DR) is the most common and serious microvascular complication in the diabetic population. Using computer-aided diagnosis from the fundus images has become a method of detecting retinal diseases, but the detection of multiple lesions is still a difficult point in current research. Methods This study proposed a multi-label classification method based on the graph convolutional network (GCN), so as to detect 8 types of fundus lesions in color fundus images. We collected 7459 fundus images (1887 left eyes, 1966 right eyes) from 2282 patients (1283 women, 999 men), and labeled 8 types of lesions, laser scars, drusen, cup disc ratio ($$C/D>0.6$$ C / D > 0.6 ), hemorrhages, retinal arteriosclerosis, microaneurysms, hard exudates and soft exudates. We constructed a specialized corpus of the related fundus lesions. A multi-label classification algorithm for fundus images was proposed based on the corpus, and the collected data were trained. Results The average overall F1 Score (OF1) and the average per-class F1 Score (CF1) of the model were 0.808 and 0.792 respectively. The area under the ROC curve (AUC) of our proposed model reached 0.986, 0.954, 0.946, 0.957, 0.952, 0.889, 0.937 and 0.926 for detecting laser scars, drusen, cup disc ratio, hemorrhages, retinal arteriosclerosis, microaneurysms, hard exudates and soft exudates, respectively. Conclusions Our results demonstrated that our proposed model can detect a variety of lesions in the color images of the fundus, which lays a foundation for assisting doctors in diagnosis and makes it possible to carry out rapid and efficient large-scale screening of fundus lesions.

Population Policies in Turkey and Demographic Changes on a Social Map

2016 ◽  
Vol 6 (2) ◽  
pp. 240-266 ◽  
Author(s):  
Mustafa Murat Yucesahin ◽  
Tuğba Adalı ◽  
A Sinan Türkyılmaz
Keyword(s):  
Population Policy ◽  
Developed Countries ◽  
Ageing Population ◽  
Demographic Changes ◽  
Demographic Transitions ◽  
Population Policies ◽  
Demographic Indicators ◽  
The Social ◽  
Working Age ◽  
Low Levels

Compared to its past structure, Turkey is now a country with low levels of fertility and mortality. This junction that Turkey now has reached is associated with a number of risks, such as an ageing population, and a decreasing working-age population. The antinatalist policy era of Turkey was followed by a period of maintenance, yet the recent demographic changes formed the basis of a pronatalist population policy from the government’s view. This study discusses the link between demographic change and population policies in Turkey. It further aims to position Turkey spatially in relation to selected countries that are in various stages of their demographic transitions with different population policies, using a multidimensional scaling approach with data on 25 selected countries from the UN. The analysis is based on a 34-year period, 1975-2009, so as to better demonstrate Turkey’s international position on a social map, past and present. Our findings suggest that Turkey’s position on the social map shifted towards developed countries over time in terms of demographic indicators and population policies. 

To the comparative analysis of the digitalization process of state administration in Russia and other countries

2020 ◽  
pp. 75-117
Author(s):  
A.N. Shvetsov
Keyword(s):  
Public Administration ◽  
Information And Communication Technologies ◽  
Large Scale ◽  
Communication Technologies ◽  
Developed Countries ◽  
Electronic Government ◽  
Digital Government ◽  
Information And Communication ◽  
The Developed Countries ◽  
Comprehensive Programs

The article compares the processes of dissemination of modern information and communication technologies in government bodies in Russia and abroad. It is stated that Russia began the transition to «electronic government» later than the developed countries, in which this process was launched within the framework of large-scale and comprehensive programs for reforming public administration in the 1980s and 1990s. However, to date, there is an alignment in the pace and content of digitalization tasks. At a new stage in this process, the concept of «electronic government» under the influence of such newest phenomena of the emerging information society as methods of analysis of «big data», «artificial intelligence», «Internet of things», «blockchain» is being transformed into the category of «digital government». Achievements and prospects of public administration digitalization are considered on the example of countries with the highest ratings — Denmark, Australia, Republic of Korea, Great Britain, USA and Russia.

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