Eye Disease Image Dataset

1. Worldwide, eye ailments are recognized as significant contributors to nonfatal disabling conditions. In Bangladesh, 1.5% of adults suffer from blindness, while 21.6% experience low vision. Therefore, eye disease detection is crucial for preserving vision, preventing blindness, and maintaining overall health. Early detection allows for prompt intervention and treatment, preventing irreversible damage and preserving quality of life. By analyzing the dataset, researchers will be able to identify trends, develop algorithms for diagnosis, assess treatment effectiveness, and inform preventive measures.

2. Currently, computer vision methods show great promise in carrying out classification and detection tasks of this nature.

3. To develop computer vision-based algorithms, an extensive eye disease dataset is presented containing original and augmented datasets of a variety of eye diseases such as Retinitis Pigmentosa, Retinal Detachment, Pterygium, Myopia, Macular Scar, Glaucoma, Disc Edema, Diabetic Retinopathy, Central Serous Chorioretinopathy, and Healthy eye image. The classifications of this dataset are done with the help of a domain expert from a healthcare institute.

4. A total of 5335 images of healthy and affected eye images were collected from Anwara Hamida Eye Hospital in Faridpur and BNS Zahrul Haque Eye Hospital in Faridpur district with the help of the hospital authorities. Then from these original images, a total of 16242 augmented images are produced by using Rotation, Width shifting, Height shifting, Translation, Flipping, and Zooming techniques to increase the number of data.

1. 全球范围内，眼部疾病已被认定为引发非致死性致残病症的重要诱因。在孟加拉国，1.5%的成年人遭受失明困扰，另有21.6%的人群存在低视力问题。因此，眼部疾病检测对于保护视力、预防失明以及维持整体健康至关重要。早期检测可实现及时干预与治疗，避免不可逆的视力损伤，保障生活质量。通过对该数据集开展分析，研究人员能够识别疾病流行趋势、开发诊断算法、评估治疗效果，并为制定预防措施提供科学依据。
2. 当前，计算机视觉方法在承担此类分类与检测任务方面展现出显著的应用潜力。
3. 为开发基于计算机视觉的算法，本研究构建了大规模眼部疾病数据集，其中包含多种眼部疾病的原始图像与增强图像，涵盖色素性视网膜炎（Retinitis Pigmentosa）、视网膜脱离（Retinal Detachment）、翼状胬肉（Pterygium）、近视（Myopia）、黄斑瘢痕（Macular Scar）、青光眼（Glaucoma）、视盘水肿（Disc Edema）、糖尿病视网膜病变（Diabetic Retinopathy）、中心性浆液性脉络膜视网膜病变（Central Serous Chorioretinopathy）以及健康眼部图像。该数据集的分类工作由来自医疗机构的领域专家协助完成。
4. 研究团队从法里德布尔地区的Anwara Hamida眼科医院与BNS Zahrul Haque眼科医院获取了共计5335张健康眼部与患病眼部的原始图像，过程中获得了两家医院管理方的协助。随后，研究人员通过旋转、宽度平移、高度平移、平移、翻转以及缩放等数据增强技术，从这些原始图像中生成了共计16242张增强图像，以扩充数据集规模。