Data for: Improved accuracy in OCT diagnosis of rare retinal disease using few-shot learning with generative adversarial networks

The retinal OCT images ofr rare diseases were extracted by using the Google image and Google dataset search that included English keywords including central serous chorioretinopathy (CSC), macular telangiectasia (MacTel), macular hole (MH), Stargardt disease, retinitis pigmentosa (RP). These rare diseases were selected according to a previous review article about OCT diagnosis. The images possessing rare diseases were manually classified by two board-certified ophthalmologists, and ambiguous images were removed to clarify the image domains.

Additional file "Segmentation_manual.zip" offers manually segmentedOCT images for pathologic lesions.

罕见疾病的视网膜OCT图像通过Google图像和Google数据集搜索提取，关键词包括中心性浆液性脉络膜视网膜病变（CSC）、黄斑脉络膜视网膜病变（MacTel）、黄斑孔（MH）、Stargardt病、视网膜色素变性（RP）。这些罕见疾病是根据一篇关于OCT诊断的先前综述文章进行选定的。具有罕见疾病特征的图像由两位执业眼科医生进行手动分类，并移除模糊图像以明确图像领域。附加文件“Segmentation_manual.zip”提供了病理病变的手动分割OCT图像。