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Accurate medical image analysis can greatly assist clinical diagnosis, but its effectiveness relies on high-quality expert annotations Obtaining pixel-level labels for medical images, particularly fundus images, remains costly and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Xi Luo , Shixin Xu , Ying Xie , JianZhong Hu , Yuwei He , Yuhui Deng , Huaxiong Huang

Diabetic Retinopathy (DR), a leading cause of vision impairment, requires early detection and treatment. Developing robust AI models for DR classification holds substantial potential, but a key challenge is ensuring their generalization in…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Sanoojan Baliah , Fadillah A. Maani , Santosh Sanjeev , Muhammad Haris Khan

Diabetic retinopathy (DR) is a primary cause of blindness in working-age people worldwide. About 3 to 4 million people with diabetes become blind because of DR every year. Diagnosis of DR through color fundus images is a common approach to…

Computer Vision and Pattern Recognition · Computer Science 2020-03-27 Qilei Chen , Ping Liu , Jing Ni , Yu Cao , Benyuan Liu , Honggang Zhang

Automatic diabetic retinopathy (DR) grading based on fundus photography has been widely explored to benefit the routine screening and early treatment. Existing researches generally focus on single-field fundus images, which have limited…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Junlin Hou , Jilan Xu , Fan Xiao , Rui-Wei Zhao , Yuejie Zhang , Haidong Zou , Lina Lu , Wenwen Xue , Rui Feng

Artificial intelligence algorithms have demonstrated their image classification and segmentation ability in the past decade. However, artificial intelligence algorithms perform less for actual clinical data than those used for simulations.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Mostafa Hajighasemlou , Samad Sheikhaei , Hamid Soltanian-Zadeh

Longitudinal imaging is able to capture both static anatomical structures and dynamic changes in disease progression towards earlier and better patient-specific pathology management. However, conventional approaches for detecting diabetic…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Rachid Zeghlache , Pierre-Henri Conze , Mostafa El Habib Daho , Ramin Tadayoni , Pascal Massin , Béatrice Cochener , Gwenolé Quellec , Mathieu Lamard

Diabetic retinopathy (DR) is the primary cause of vision loss among grownup people around the world. In four out of five cases having diabetes for a prolonged period leads to DR. If detected early, more than 90 percent of the new DR…

Computer Vision and Pattern Recognition · Computer Science 2020-06-16 Niloy Sikder , Md. Sanaullah Chowdhury , Abu Shamim Mohammad Arif , Abdullah-Al Nahid

In this paper, we propose an explainable and interpretable diabetic retinopathy (ExplainDR) classification model based on neural-symbolic learning. To gain explainability, a highlevel symbolic representation should be considered in decision…

Machine Learning · Computer Science 2022-04-05 Se-In Jang , Michael J. A. Girard , Alexandre H. Thiery

Diabetic retinopathy (DR) is a leading cause of vision loss, requiring early and accurate assessment to prevent irreversible damage. Spectral Domain Optical Coherence Tomography (SD-OCT) enables high-resolution retinal imaging, but…

Image and Video Processing · Electrical Eng. & Systems 2025-07-15 S. Chen , D. Ma , M. Raviselvan , S. Sundaramoorthy , K. Popuri , M. J. Ju , M. V. Sarunic , D. Ratra , M. F. Beg

Recent studies suggest that early stages of diabetic retinopathy (DR) can be diagnosed by monitoring vascular changes in the deep vascular complex. In this work, we investigate a novel method for automated DR grading based on optical…

Image and Video Processing · Electrical Eng. & Systems 2022-12-22 Linus Kreitner , Ivan Ezhov , Daniel Rueckert , Johannes C. Paetzold , Martin J. Menten

Purpose: To demonstrate that retinal microvasculature per se is a reliable biomarker for Diabetic Retinopathy (DR) and, by extension, cardiovascular diseases. Methods: Deep Learning Convolutional Neural Networks (CNN) applied to color…

Image and Video Processing · Electrical Eng. & Systems 2021-07-29 Anusua Trivedi , Jocelyn Desbiens , Ron Gross , Sunil Gupta , Rahul Dodhia , Juan Lavista Ferres

Fundus photography (FP) remains the primary imaging modality in screening various retinal diseases including age-related macular degeneration, diabetic retinopathy and glaucoma. FP allows the clinician to examine the ocular fundus…

Image and Video Processing · Electrical Eng. & Systems 2023-02-21 Shanmukh Reddy Manne , Jose-Alain Sahel , Jay Chhablani , Kiran Kumar Vupparaboinab , Soumya Jana

Diabetic Retinopathy (DR) is a leading cause of vision loss around the world. To help diagnose it, numerous cutting-edge works have built powerful deep neural networks (DNNs) to automatically grade DR via retinal fundus images (RFIs).…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Yupeng Cheng , Qing Guo , Felix Juefei-Xu , Huazhu Fu , Shang-Wei Lin , Weisi Lin

Diabetic Retinopathy (DR) is a prominent cause of blindness in the world. The early treatment of DR can be conducted from detection of microaneurysms (MAs) which appears as reddish spots in retinal images. An automated microaneurysm…

Computer Vision and Pattern Recognition · Computer Science 2018-07-10 Noushin Eftekheri , Mojtaba Masoudi , Hamidreza Pourreza , Kamaledin Ghiasi Shirazi , Ehsan Saeedi

The quality of diabetic retinopathy (DR) screening relies on the ability to correctly grade severity; however, many deep-learning (DL) classifiers cannot be easily interpreted in the clinical context. This study presents a methodology that…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Pir Bakhsh Khokhar , Carmine Gravino , Fabio Palomba , Sule Yildirim Yayilgan , Sarang Shaikh

Diabetic retinopathy (DR) and diabetic macular edema (DME) are leading causes of preventable blindness among working-age adults. Traditional approaches in the literature focus on standard color fundus photography (CFP) for the detection of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Pablo Jimenez-Lizcano , Sergio Romero-Tapiador , Ruben Tolosana , Aythami Morales , Guillermo González de Rivera , Ruben Vera-Rodriguez , Julian Fierrez

Diabetic retinopathy (DR) is a complication of diabetes, and one of the major causes of vision impairment in the global population. As the early-stage manifestation of DR is usually very mild and hard to detect, an accurate diagnosis via…

Computer Vision and Pattern Recognition · Computer Science 2022-12-14 Yuhan Zheng , Fuping Wu , Bartłomiej W. Papież

Diabetic Retinopathy (DR) is a severe complication of diabetes that can cause blindness. Although effective treatments exist (notably laser) to slow the progression of the disease and prevent blindness, the best treatment remains prevention…

Image and Video Processing · Electrical Eng. & Systems 2022-11-22 Yihao Li , Rachid Zeghlache , Ikram Brahim , Hui Xu , Yubo Tan , Pierre-Henri Conze , Mathieu Lamard , Gwenolé Quellec , Mostafa El Habib Daho

Many eye diseases like Diabetic Macular Edema (DME), Age-related Macular Degeneration (AMD), and Glaucoma manifest in the retina, can cause irreversible blindness or severely impair the central version. The Optical Coherence Tomography…

Image and Video Processing · Electrical Eng. & Systems 2023-03-10 Nchongmaje Ndipenoch , Alina Miron , Zidong Wang , Yongmin Li

This paper proposes the importance of age and gender information in the diagnosis of diabetic retinopathy. We utilized Deep Residual Neural Networks (ResNet) and Densely Connected Convolutional Networks (DenseNet), which are proven…

Image and Video Processing · Electrical Eng. & Systems 2023-02-14 Long Bai , Sihang Chen , Mingyang Gao , Leila Abdelrahman , Manal Al Ghamdi , Mohamed Abdel-Mottaleb