Advanced Diabetic Retinopathy Classification: Integrating Pathological Indicators Segmentation and Morphological Feature Analysis

Published: 01 Jan 2024, Last Modified: 13 Nov 2024OMIA@MICCAI 2024EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Diabetic retinopathy (DR) is a common and serious complication of diabetes mellitus, often leading to blindness. Identifying DR stages accurately is essential for timely and effective treatment. This study introduces an innovative method to improve DR classification by detecting retinal lesions in fundus images (such as Hard Exudates, Soft Exudates, Microaneurysms, and Hemorrhages) and extracting visual and morphological features from these lesions. The proposed approach generates synthetic retinal lesions and creates artificial masks to highlight DR pathology regions. A segmentation model is trained to produce these masks, which are then refined using real fundus images and corresponding annotations. The model is then fine-tuned with real fundus images and corresponding masks. The model then derives morphological features (such as the number of each lesion, and maximum and minimum sizes, among others) from the generated masks and integrates them with latent features extracted from the segmentation model to enhance classification accuracy. The model can show a visual explanation generated by the to aid doctors in verifying and trusting the AI’s decisions, ultimately enhancing clinical decision-making and patient care. Experimental results on the DDR, E-Ophtha, and IDRiD datasets demonstrate the method’s effectiveness in improving lesion segmentation and DR classification. The DR classification achieved an accuracy of 88.04% and a Quadratic Weighted Kappa (QWK) score of 93.71%, surpassing state-of-the-art methods. The use of composite masks improves the model’s ability to identify subtle DR progression indicators, enabling more precise diagnostics and explainable AI-based interventions in clinical practice. The code is publicly available at https://github.com/saifalkhaldiurv/Advanced-Diabetic-retinopathy-Classification.git.
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