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Gzip Archive - 2.1 GB -
MD5: bb058e52bfcfde3995afea4234474844
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Gzip Archive - 2.1 GB -
MD5: 663f86bb5fbd357047eaac0c321509d6
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Gzip Archive - 2.3 GB -
MD5: eb8087b85896c3a7d98bc149c5e226c8
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Gzip Archive - 2.3 GB -
MD5: e8c046446e4a8a14112c4f81e97eee08
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Gzip Archive - 2.3 GB -
MD5: 933f6bc010c1d04e1e907926ccb57b5d
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Gzip Archive - 2.4 GB -
MD5: 5e9d41b46f48fb233cbcec61d4647c9d
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Nov 6, 2024
Tomar, Dhananjay, 2024, "Replication Data for: Are nuclear masks all you need for improved out-of-domain generalization? A closer look at cancer classification in histopathology", https://doi.org/10.18710/NXPLFL, DataverseNO, V1
This dataset is a processed version of the CAMELYON17 dataset used in the NeurIPS 2024 paper "Are nuclear masks all you need for improved out-of-domain generalization? A closer look at cancer classification in histopathology". It consists of patches / tiles from 50 Whole Slide Images (WSIs) (10 WSIs from each of the 5 hospitals) in the CAMELYON17 d... |
Plain Text - 5.6 KB -
MD5: 566f57729ce97e88c3020c473865769d
README file |
Comma Separated Values - 29.1 MB -
MD5: b144dd3e8fac32f26d9e585958c7b25d
Metadata info for the files inside the tar file. Metadata has columns patient,node,x_coord,y_coord,tumor,slide,center,split
Each row starts with index of the row followed by data for the columns listed above. Column "tumor" refers to whether the patch/tile has tumor or not. "split" is "0" for trainnig and "1" for validation dataset split. "center"... |
TAR Archive - 1.2 GB -
SHA1: 3c79321a29a22c93641e7d0d2ca9ace9b9d7f76c
Patches for the WSI patient_004_node_4 |
