…The Task 1 challenge dataset for lesion segmentation contains 2,000 images for training with ground truth segmentations (2000 binary mask images).
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…microaneurysm, intraretinal hemorrhage, hard exudate, cotton-wool spot, vitreous hemorrhage, preretinal hemorrhage, neovascularization and fibrous proliferation; Over 34K expert-labeled pixel-level lesion segments ; Multi-task, i.e., lesion segmentation, lesion classification, and DR grading.
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…This Task 1 dataset is the challenge on lesion segmentation. It includes 2594 images.
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…The images of the dataset were extracted from the public databases DermIS and DermQuest, along with manual segmentations of the lesions. Clausi, "Automatic segmentation of skin lesions from dermatological photographs using a joint probabilistic texture distinctiveness approach", IEEE Transactions on Biomedical Engineering [2] Amelard, R
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Introduced by Da et al. in DigestPath: a Benchmark Dataset with Challenge Review for the Pathological Detection and Segmentation of Digestive-System Grand-Challenge Page 1. Colonoscopy tissue segment dataset Colonoscopy pathology examination can find cells of early-stage colon tumor from small tissue slices. Here we propose a challenge task on automatic colonoscopy tissue segmentation and screening, aiming at automatic lesion segmentation and classification of the whole tissue (benign vs. malignant). DigestPath: a Benchmark Dataset with Challenge Review for the Pathological Detection and Segmentation of Digestive-System[J]. Medical Image Analysis, 2022: 102485.
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…The PH² dataset has been developed for research and benchmarking purposes, in order to facilitate comparative studies on both segmentation and classification algorithms of dermoscopic images.
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