Dataset Information

DMENet: Diabetic Macular Edema diagnosis using Hierarchical Ensemble of CNNs.

ABSTRACT: Diabetic Macular Edema (DME) is an advanced stage of Diabetic Retinopathy (DR) and can lead to permanent vision loss. Currently, it affects 26.7 million people globally and on account of such a huge number of DME cases and the limited number of ophthalmologists, it is desirable to automate the diagnosis process. Computer-assisted, deep learning based diagnosis could help in early detection, following which precision medication can help to mitigate the vision loss. METHOD:In order to automate the screening of DME, we propose a novel DMENet Algorithm which is built on the pillars of Convolutional Neural Networks (CNNs). DMENet analyses the preprocessed color fundus images and passes it through a two-stage pipeline. The first stage detects the presence or absence of DME whereas the second stage takes only the positive cases and grades the images based on severity. In both the stages, we use a novel Hierarchical Ensemble of CNNs (HE-CNN). This paper uses two of the popular publicly available datasets IDRiD and MESSIDOR for classification. Preprocessing on the images is performed using morphological opening and gaussian kernel. The dataset is augmented to solve the class imbalance problem for better performance of the proposed model. RESULTS:The proposed methodology achieved an average Accuracy of 96.12%, Sensitivity of 96.32%, Specificity of 95.84%, and F-1 score of 0.9609 on MESSIDOR and IDRiD datasets. CONCLUSION:These excellent results establish the validity of the proposed methodology for use in DME screening and solidifies the applicability of the HE-CNN classification technique in the domain of biomedical imaging.

SUBMITTER: Singh RK

PROVIDER: S-EPMC7010263 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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DMENet: Diabetic Macular Edema diagnosis using Hierarchical Ensemble of CNNs.

Singh Rajeev Kumar RK Gorantla Rohan R

PloS one 20200210 2

Diabetic Macular Edema (DME) is an advanced stage of Diabetic Retinopathy (DR) and can lead to permanent vision loss. Currently, it affects 26.7 million people globally and on account of such a huge number of DME cases and the limited number of ophthalmologists, it is desirable to automate the diagnosis process. Computer-assisted, deep learning based diagnosis could help in early detection, following which precision medication can help to mitigate the vision loss.<h4>Method</h4>In order to autom ...[more]

PMID: 32040475

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Project description:BackgroundThe relative efficacy and safety of intravitreous aflibercept, bevacizumab, and ranibizumab in the treatment of diabetic macular edema are unknown.MethodsAt 89 clinical sites, we randomly assigned 660 adults (mean age, 61±10 years) with diabetic macular edema involving the macular center to receive intravitreous aflibercept at a dose of 2.0 mg (224 participants), bevacizumab at a dose of 1.25 mg (218 participants), or ranibizumab at a dose of 0.3 mg (218 participants). The study drugs were administered as often as every 4 weeks, according to a protocol-specified algorithm. The primary outcome was the mean change in visual acuity at 1 year.ResultsFrom baseline to 1 year, the mean visual-acuity letter score (range, 0 to 100, with higher scores indicating better visual acuity; a score of 85 is approximately 20/20) improved by 13.3 with aflibercept, by 9.7 with bevacizumab, and by 11.2 with ranibizumab. Although the improvement was greater with aflibercept than with the other two drugs (P<0.001 for aflibercept vs. bevacizumab and P=0.03 for aflibercept vs. ranibizumab), it was not clinically meaningful, because the difference was driven by the eyes with worse visual acuity at baseline (P<0.001 for interaction). When the initial visual-acuity letter score was 78 to 69 (equivalent to approximately 20/32 to 20/40) (51% of participants), the mean improvement was 8.0 with aflibercept, 7.5 with bevacizumab, and 8.3 with ranibizumab (P>0.50 for each pairwise comparison). When the initial letter score was less than 69 (approximately 20/50 or worse), the mean improvement was 18.9 with aflibercept, 11.8 with bevacizumab, and 14.2 with ranibizumab (P<0.001 for aflibercept vs. bevacizumab, P=0.003 for aflibercept vs. ranibizumab, and P=0.21 for ranibizumab vs. bevacizumab). There were no significant differences among the study groups in the rates of serious adverse events (P=0.40), hospitalization (P=0.51), death (P=0.72), or major cardiovascular events (P=0.56).ConclusionsIntravitreous aflibercept, bevacizumab, or ranibizumab improved vision in eyes with center-involved diabetic macular edema, but the relative effect depended on baseline visual acuity. When the initial visual-acuity loss was mild, there were no apparent differences, on average, among study groups. At worse levels of initial visual acuity, aflibercept was more effective at improving vision. (Funded by the National Institutes of Health; ClinicalTrials.gov number, NCT01627249.).

Dataset Information

DMENet: Diabetic Macular Edema diagnosis using Hierarchical Ensemble of CNNs.

Publications

DMENet: Diabetic Macular Edema diagnosis using Hierarchical Ensemble of CNNs.

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