Aug 2026· Journal of imaging informatics in medicine· 0 citations· 26 references
Medicine
TL;DR
A multimodal fundus disease diagnosis method based on progressive optimization of probabilistic correspondences is proposed, which achieves improved accuracy and Cohen's kappa under public benchmark settings, and demonstrates robustness under the evaluated noise perturbation and limited-data scenarios.
Retinal disorders are the leading cause of partial and permanent vision loss across the globe, making early diagnosis and timely intervention paramount for effective treatment planning. Recent deep learning methods for retinal disease diagnosis from fundus images acquired using optical imaging sensors primarily focus o...
The precise and prompt identification of ocular conditions, such as diabetic retinopathy (DR), diabetic macular edema (DME), or glaucoma, often depends on the collaborative analysis of medical imaging techniques such as fundus photography or optical coherence tomography (OCT), alongside the patient’s demographic and ac...
A. Mutawa, K. Sabti, Bibin Shalini Sundaram Thankaleela et al.· Computers· 0 citations
A systematic comparative evaluation of three deep learning-based segmentation architectures — U-Net, U-Net++, and Y-Net — for automated identification of DME and Intraretinal Fluid regions in OCT scans demonstrates the feasibility of deep learning-based OCT segmentation as a diagnostic support tool in resource-constrai...
Dhiraj Pyakurel, Yokisha Poudel, Sushiksha Prasai et al.· Journal of Hillside College...· 0 citations
Traditional systems of ocular disease diagnosis and many deep learning-based systems are limited in their practice to analyzing fundus images from a single eye, often using raw, unprocessed data. This fails to include the critical correlation between bilateral eyes, has several issues such as low image contrast, noise,...
Amanulla Mohammad, N. Ramakrishnaiah· Computers in Biology and Med...· 0 citations
Automated analysis of retinal fundus photographs has become an important research direction for computer-aided ophthalmic screening. However, many existing deep-learning studies focus on a single disease, particularly diabetic retinopathy, or emphasize disease presence without integrating severity assessment. This stud...
S. Shinde· Journal of Intelligent Decis...· 0 citations
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