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README.md
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**Pixel Annotations of TCGA-RCC and TCGA-LU**: are saved as PNG files, the region marked by white/red/green is the cancer region, and marked by blue is the abandoned region, which also can be regarded as background.
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The PNG file name is the case_id of each WSI. Match the original TCGA name with dataset_csv files in our GitHub repo
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Each annotation mask's size equals level 3 of the corresponding WSI.
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**Patch Annotations of TCGA-STAD**: are saved as CSV files, each raw indicates a patch with corresponding coordinates, sizes, and annotated labels.
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**Pixel Annotations of TCGA-RCC and TCGA-LU**: are saved as PNG files, the region marked by white/red/green is the cancer region, and marked by blue is the abandoned region, which also can be regarded as background.
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The PNG file name is the case_id of each WSI. Match the original TCGA name with dataset_csv files in [our GitHub repo](https://github.com/ZeyuGaoAi/SMMILe/tree/main/single/dataset_csv).
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Each annotation mask's size equals level 3 of the corresponding WSI.
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**Patch Annotations of TCGA-STAD**: are saved as CSV files, each raw indicates a patch with corresponding coordinates, sizes, and annotated labels.
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Both coordinates and sizes are obtained at the maximum magnification of the corresponding SVS file.
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The CSV file name is the case_id of each WSI. Match the original TCGA name with dataset_csv files in [our GitHub repo](https://github.com/ZeyuGaoAi/SMMILe/blob/main/multi/dataset_csv/gastric_subtyping_npy.csv).
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The fine-grained subtype labels of WSIs can be obtained by counting whether patches of certain subtypes appear in each WSI.
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