Domain Adaptation for 2D Medical Image Segmentation
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This dataset includes two 2D medical image segmentation benchmark.1. OD/OC Segmentation in Fundus ImageThis dataset conprises five sub-datasets: Drishti-GS, RIM-ONE-r3, ORIGA, REFUGE, and the validation set of REFUGE2. Each image is cropped around the optic disc area. The size of all images is 512×512. The manual pixel-wise annotation is stored as a PNG image with the same size as the corresponding fundus image with the following labels:128: Optic Disc (Grey color)0: Optic Cup (Black color)255: Background (White color)2. Polyp Segmentation in Endoscopy ImageThis dataset conprises four sub-datasets: BKAI, CVC-ClinicDB, ETIS-LaribPolypDB, and Kvasir-SEG. The manual pixel-wise annotation is stored as a PNG image with the same size as the corresponding fundus image with the following labels:255: Polyp (White color)0: Background (Black color)
本数据集包含两个二维医学图像分割基准。1. 视网膜图像中的OD/OC分割本数据集由五个子数据集组成：Drishti-GS、RIM-ONE-r3、ORIGA、REFUGE及其验证集。每个图像均围绕视盘区域进行裁剪。所有图像的尺寸均为512×512。手动像素级标注以PNG图像的形式存储，其尺寸与相应的视网膜图像相同，并包含以下标签：128：视盘（灰色）0：视杯（黑色）255：背景（白色）。2. 内镜图像中的息肉分割本数据集由四个子数据集组成：BKAI、CVC-ClinicDB、ETIS-LaribPolypDB和Kvasir-SEG。手动像素级标注以PNG图像的形式存储，其尺寸与相应的视网膜图像相同，并包含以下标签：255：息肉（白色）0：背景（黑色）
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IEEE Dataport
