18 datasets found

SUSTech-SYSU dataset is a collection of images of diabetic retinopathy.

The dataset used for the proposed Concept-Centric Visual Turing Test (VTT) framework for evaluating MIC methods.

MAPLES-DR is a dataset containing new diagnoses for Diabetic Retinopathy (DR) and Macular Edema (ME) as well as new pixel-wise segmentation maps for 10 anatomical and...

The APTOS 2019 blindness detection competition dataset is used for training and testing the proposed Frequency Domain Convolutional Neural Network (FDCNN) architecture.

A dataset of retinal images for diabetic retinopathy grading.

The DRAC dataset for diabetic retinopathy analysis

The ultra-wide OCTA dataset for diabetic retinopathy analysis

Retinal fundus images have been extensively used for clinical analysis of various ocular diseases, but the quality of fundus images is critical to the diagnosis and screening of...

The DRIVE dataset includes 40 color fundus photographs divided into two parts: 20 training images and 20 test images with manual segmentation of the vessels and binary masks of...

The dataset used in the diabetic retinopathy detection task in the conformal risk control framework.

Diabetic Retinopathy dataset containing 1000 color fundus images from KAGGLE

The APTOS-2019 blindness detection dataset is used for detecting diabetic retinopathy severity stages from fundus images.

The Kaggle-DR dataset is used for diabetic retinopathy grading, containing 35,126 high-resolution fundus images.

The dataset used for medical image synthesis using Generative Adversarial Networks (GANs).

The dataset used for the diabetic retinopathy diagnosis and uncertainty quantification task.

The EyePACS dataset consists of 35,126 training images and 53,576 testing images only containing grading labels.

Diabetic retinopathy (DR) is a leading cause of vision loss in the world and numerous cutting-edge works have built powerful deep neural networks (DNNs) to automatically...

The dataset used in this paper is not explicitly described. However, it is mentioned that the authors used a dataset for medical image classification, specifically for diabetic...