AIMC Topic: Retinal Diseases
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Retinal image-based disease classification using hybrid deep architecture with improved image features.
International ophthalmology
Aug 5, 2025
OBJECTIVE: Ophthalmologists use retinal fundus imaging as a useful tool to diagnose retinal issues. Recently, research on machine learning has concentrated on disease diagnosis. However, disease detection is less accurate, more likely to be misidenti...
Multi-modal classification of retinal disease based on convolutional neural network.
Biomedical physics & engineering express
Jul 28, 2025
Retinal diseases such as age-related macular degeneration and diabetic retinopathy will lead to irreversible blindness without timely diagnosis and treatment. Optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) imag...
Advances in machine learning for ABCA4-related retinopathy: segmentation and phenotyping.
International ophthalmology
Jul 23, 2025
PURPOSE: Stargardt disease, also called ABCA4-related retinopathy (ABCA4R), is the most common form of juvenile-onset macular dystrophy and yet lacks an FDA approved treatment. Substantial progress has been made through landmark studies like that of ...
A deep learning model for diagnosis of inherited retinal diseases.
Scientific reports
Jul 2, 2025
To evaluate the performance of a multi-input deep learning (DL) model in detecting two common inherited retinal diseases (IRDs), i.e. retinitis pigmentosa (RP) and Stargardt disease (STGD), and differentiating them from healthy eyes. This cross-secti...
Realistic fundus photograph generation for improving automated disease classification.
The British journal of ophthalmology
Jun 23, 2025
AIMS: This study aims to investigate whether denoising diffusion probabilistic models (DDPMs) could generate realistic retinal images, and if they could be used to improve the performance of a deep convolutional neural network (CNN) ensemble for mult...
Advances in disease detection through retinal imaging: A systematic review.
Computers in biology and medicine
Jun 6, 2025
Ocular and non-ocular diseases significantly impact millions of people worldwide, leading to vision impairment or blindness if not detected and managed early. Many individuals could be prevented from becoming blind by treating these diseases early on...
The potential of artificial intelligence reading label system on the training of ophthalmologists in retinal diseases, a multicenter bimodal multi-disease study.
BMC medical education
Apr 8, 2025
OBJECTIVE: To assess the potential of artificial intelligence reading label system on the training of ophthalmologists in a multicenter bimodal multi-disease study.
Retinal OCT image segmentation with deep learning: A review of advances, datasets, and evaluation metrics.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 4, 2025
Optical coherence tomography (OCT) is a widely used imaging technology in ophthalmic clinical practice, providing non-invasive access to high-resolution retinal images. Segmentation of anatomical structures and pathological lesions in retinal OCT ima...
Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Fundus disease is a complex and universal disease involving a variety of pathologies. Its early diagnosis using fundus images can effectively prevent further diseases and provide targeted treatment plans for patients. Recent deep learning models for ...
Integrating lightweight convolutional neural network with entropy-informed channel attention and adaptive spatial attention for OCT-based retinal disease classification.
Computers in biology and medicine
Apr 1, 2025
This article proposes an effective and lightweight contextual convolutional neural network architecture called LOCT-Net for classifying retinal diseases. The LOCT-Net adopts nested residual blocks to capture the local patterns from the optical cohere...
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