Metadata-Version: 2.4
Name: ISPY2-pCR-dataset
Version: 0.0.6
Summary: Dataset curation pipeline for ISPY2 pCR prediction
Author-email: Johannes Kiechle <johannes.kiechle@tum.de>
License-Expression: MIT
Project-URL: Homepage, https://github.com/hannesk95/ISPY2-pCR-dataset
Project-URL: Issues, https://github.com/hannesk95/ISPY2-pCR-dataset/issues
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch>=2.6.0
Requires-Dist: numpy>=2.2.6
Requires-Dist: torchio>=0.20.7
Requires-Dist: tqdm>=4.67.1
Requires-Dist: torchvision>=0.21.0
Requires-Dist: tqdm>=4.67.1
Requires-Dist: pandas>=2.3.3
Requires-Dist: tcia-utils>=3.2.1
Dynamic: license-file

# ISPY2 Dataset Curation for Breast Cancer pCR Prediction

Implementation of the ISPY2 dataset curation pipeline for breast cancer pathologic complete response (pCR) prediction from our publication [&#34;Graph Representation Learning of Longitudinal Medical Imaging Trajectories for Treatment Response Prediction&#34;](https://arxiv.org/pdf/2607.04912).

## Example Usage

```python
import ISPY2_pCR_dataset.ISPY2_pCR_dataset as dataset

file_path = "path/to/tcia/manifest/xlsx/file" # can be found at https://github.com/compai-lab/2026-miccai-grail-kiechle
output_dir = "path/to/output/directory"

dataset.download_data(file_path=file_path, 
                      output_dir=output_dir)
```

## Citation

```bibtex
@article{kiechle2026graph,
title={Graph Representation Learning of Longitudinal Medical Imaging Trajectories for Treatment Response Prediction},
author={Kiechle, Johannes and Osuala, Richard and Lang, Daniel M and Fischer, Stefan M and Jan{\'\i}{\v{c}}kov{\'a}, Ivana and Lekadir, Karim and Schnabel, Julia A and Peeken, Jan C},
journal={arXiv preprint arXiv:2607.04912},
year={2026}
}
```
