Key result
GA-FCM method outperforms manual point selection for predicting retinopathy from angiography, achieving ~78% sensitivity.
Why the study?
A new computer diagnostic method integrating fuzzy C-means and genetic algorithm was developed to improve prediction of retinopathy in diabetic patients from angiography images.
Does an integrated GA-FCM method improve the prediction of retinopathy from angiography images in diabetic patients compared to manual methods?
Does an integrated GA-FCM method improve the prediction of retinopathy from angiography images in diabetic patients compared to manual methods?
An integrated genetic algorithm and fuzzy C-means approach demonstrates high sensitivity and accuracy in predicting diabetic retinopathy from angiography images.
May support automated retinopathy screening in diabetes; leaves open prospective clinical validation before adoption.
The present study is developed a new approach using a computer diagnostic method to diagnosing diabetic diseases with the use of fluorescein images. In doing so, this study presented the growth region algorithm for the aim of diagnosing diabetes, considering the angiography images of the patients' eyes. In addition, this study integrated two methods, including fuzzy C-means (FCM) and genetic algorithm (GA) to predict the retinopathy in diabetic patients from angiography images. The developed algorithm was applied to a total of 224 images of patients' retinopathy eyes. As clearly confirmed by the obtained results, the GA-FCM method outperformed the hand method regarding the selection of initial points. The proposed method showed 0.78 sensitivity. The comparison of the fuzzy fitness function in GA with other techniques revealed that the approach introduced in this study is more applicable to the Jaccard index since it could offer the lowest Jaccard distance and, at the same time, the highest Jaccard values. The results of the analysis demonstrated that the proposed method was efficient and effective to predict the retinopathy in diabetic patients from angiography images.
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Ghoushchi et al. (2021) studied Diabetic retinopathy (n=224). Genetic algorithm and fuzzy C-means (GA-FCM) method vs. Hand method was evaluated on Prediction of retinopathy (sensitivity). The GA-FCM method for predicting retinopathy from angiography images achieved a sensitivity of 0.78 and outperformed the hand method for selecting initial points.
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