MTNet-datasets.rar
Version 1A controlled experiment was conducted to test the performance of the CSP_UNet algorithm. In this paper, four commonly used retinal fundus image datasets with a total of 133 images were selected, containing DRIVE, STARE , CHASE_DB1 and HRF.The diabetic retinopathy dataset was derived from the data of the Kaggle Aptos2019 competition, and the diabetic retinopathy in each image was rated on a scale of 0 to 4: 0-normal (no DR), 1-mild, 2-moderate, 3-severe, and 4-proliferative DR, for a total of 366
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A controlled experiment was conducted to test the performance of the CSP_UNet algorithm. In this paper, four commonly used retinal fundus image datasets with a total of 133 images were selected, containing DRIVE, STARE , CHASE_DB1 and HRF.The diabetic retinopathy dataset was derived from the data of the Kaggle Aptos2019 competition, and the diabetic retinopathy in each image was rated on a scale of 0 to 4: 0-normal (no DR), 1-mild, 2-moderate, 3-severe, and 4-proliferative DR, for a total of 366