Detection of Diabetic Retinopathy (DR) Severity from Fundus Photographs: An Ensemble Approach Using Weighted Average

2022 ◽  
Author(s):  
Mulagala Sandhya ◽  
Mahesh Kumar Morampudi ◽  
Rushali Grandhe ◽  
Richa Kumari ◽  
Chandanreddy Banda ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Weighted Average ◽  
Ensemble Approach ◽  
Fundus Photographs

scholarly journals Parafoveal OCT Angiography Features in Diabetic Patients without Clinical Diabetic Retinopathy: A Qualitative and Quantitative Analysis

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Mathilde M. Goudot ◽  
Anne Sikorav ◽  
Oudy Semoun ◽  
Alexandra Miere ◽  
Camille Jung ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Quantitative Analysis ◽  
Capillary Density ◽  
Oct Angiography ◽  
Foveal Avascular Zone ◽  
Diabetic Patients ◽  
Cross Sectional ◽  
The Mean ◽  
Fundus Photographs ◽  
And Gender

Purpose. To evaluate the capacity of OCT angiography (OCTA) for detecting infraclinical lesions in parafoveal capillaries in diabetic patients without diabetic retinopathy (DR). Methods. This prospective observational cross-sectional case-control study analyzed the superficial and deep capillary plexuses (SCP and DCP) on macular OCTA scans (3 × 3 mm) centered on the fovea. We compared 22 diabetic patients (34 eyes included) without DR diagnosis on color fundus photographs, with 22 age- and gender-matched nondiabetic controls (40 eyes included). Qualitative analysis concerned morphological ischemic capillary alterations. Quantitative analysis measured foveal avascular zone (FAZ) size, parafoveal capillary density, and enlargement coefficient of FAZ between SCP and DCP. Results. Neither the qualitative nor quantitative parameters were significantly different between both groups. No microaneurysms or venous tortuosity was observed in any of the analyzed images. On the SCP, the mean FAZ area was 0.322 ± 0.125 mm2 in diabetic patients and 0.285 ± 0.150 mm2 in controls, P=0.31. On the DCP, the mean FAZ area was 0.444 ± 0.153 mm2 in cases and 0.398 ± 0.138 mm2 in controls, P=0.20. Conclusion. OCTA did not detect infraclinical qualitative or quantitative differences in parafoveal capillaries of diabetic patients without DR in comparison with nondiabetic controls.

Abstract 154: Diabetic Retinopathy and Risk of Stroke: A Secondary Analysis of Accord

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Ka-ho Wong ◽  
Cecilia Peterson ◽  
Rock Theodore ◽  
Kinga aitken ◽  
Michael Dela Cruz ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Primary Outcome ◽  
Cox Model ◽  
Secondary Analysis ◽  
Cox Models ◽  
Interaction Terms ◽  
Increased Risk ◽  
Microvascular Pathology ◽  
Fundus Photographs

Background: Diabetic retinopathy is a common microvascular complication of diabetes. Previous research has shown that the macrovascular complications of diabetes, including stroke, are often comorbid with shared and, possibly, synergistic pathology. Methods: This is a secondary analysis of the subgroup of patients who enrolled in the ACCORD Eye study of ACCORD. The primary outcome is stroke during follow-up. The primary predictor was presence of diabetic retinopathy on the Early Treatment Diabetic Retinopathy Study Severity Scale as assessed from seven-field stereoscopic fundus photographs at study baseline. We fit adjusted Cox models to the primary outcome to provide hazard ratios for stroke and included interaction terms with the ACCORD randomization arms. Results: We included 2,828 patients with a mean (SD) age of 62.1 years and 61.8% were male. The primary outcome of stroke was met by 117 patients during a mean (SD) of 5.4 (1.8) years of follow-up. Diabetic retinopathy was present in 874/2,828 (30.9%) of patients at baseline, and was more common in patients with stroke versus without stroke (41.0 vs 30.5%, p=0.016). In the Cox model, adjusted for baseline patient age, gender, race, total cholesterol, Hgb A1c, smoking, and randomization arm, we found that diabetic retinopathy remained associated with incident stroke (HR 1.60, 95% CI 1.10-2.32, p=0.015) (Figure 1). This association was not affected by randomization to the ACCORD glucose intervention (p=0.305), lipid intervention (p=0.546), or blood pressure intervention (p=0.422). Conclusion: Diabetic retinopathy is associated with an increased risk of stroke, which suggests that the microvascular pathology inherent to diabetic retinopathy has larger cardiovascular implications.

scholarly journals A Deep Learning Ensemble Approach for Diabetic Retinopathy Detection

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 150530-150539 ◽  
Author(s):  
Sehrish Qummar ◽  
Fiaz Gul Khan ◽  
Sajid Shah ◽  
Ahmad Khan ◽  
Shahaboddin Shamshirband ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Ensemble Approach

scholarly journals An Approach to Automatic Hard Exudate Detection in Retina Color Images by a Telemedicine System Based on the d-Eye Sensor and Image Processing Algorithms

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 695 ◽  
Author(s):  
Emil Saeed ◽  
Maciej Szymkowski ◽  
Khalid Saeed ◽  
Zofia Mariak
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
Ophthalmological Examination ◽  
Hard Exudate ◽  
Telemedicine System ◽  
Hard Exudates ◽  
Accuracy Level ◽  
Fundus Photographs ◽  
Classical Image ◽  
Solution Accuracy

Hard exudates are one of the most characteristic and dangerous signs of diabetic retinopathy. They can be marked during the routine ophthalmological examination and seen in color fundus photographs (i.e., using a fundus camera). The purpose of this paper is to introduce an algorithm that can extract pathological changes (i.e., hard exudates) in diabetic retinopathy. This was a retrospective, nonrandomized study. A total of 100 photos were included in the analysis—50 sick and 50 normal eyes. Small lesions in diabetic retinopathy could be automatically diagnosed by the system with an accuracy of 98%. During the experiments, the authors used classical image processing methods such as binarization or median filtration, and data was read from the d-Eye sensor. Sixty-seven patients (39 females and 28 males with ages ranging between 50 and 64) were examined. The results have shown that the proposed solution accuracy level equals 98%. Moreover, the algorithm returns correct classification decisions for high quality images and low quality samples. Furthermore, we consider taking retina photos using mobile phones rather than fundus cameras, which is more practical. The paper presents an innovative approach. The results are introduced and the algorithm is described.

Information Fusion for Diabetic Retinopathy CAD in Digital Color Fundus Photographs

2009 ◽  
Vol 28 (5) ◽  
pp. 775-785 ◽  
Author(s):  
M. Niemeijer ◽  
M.D. Abramoff ◽  
B. van Ginneken
Keyword(s):  
Diabetic Retinopathy ◽  
Information Fusion ◽  
Fundus Photographs
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