Datasets:
File size: 1,481 Bytes
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---
license: cc0-1.0
size_categories:
- 100K<n<1M
task_categories:
- image-classification
pretty_name: ' PatchCamelyon (PCam)'
tags:
- medical
- biology
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': '0'
'1': '1'
splits:
- name: train
num_bytes: 1152417815.736
num_examples: 262144
- name: validation
num_bytes: 146182832.56
num_examples: 32768
- name: test
num_bytes: 141718983.176
num_examples: 32768
download_size: 1386391969
dataset_size: 1440319631.4720001
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
# PatchCamelyon (PCam)
This is a reupload of the PatchCamelyon (PCam) dataset in jpeg/csv format instead of H5 files. The original can be found on [Github](https://github.com/basveeling/pcam).
If you use this dataset, please cite the original paper:
```bibtex
@inproceedings{veeling2018rotation,
title={Rotation Equivariant CNNs for Digital Pathology},
author={Veeling, Bastiaan S and Linmans, Jasper and Winkens, Jim and Cohen, Taco and Welling, Max},
booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part II 11},
pages={210--218},
year={2018},
organization={Springer}
}
``` |