The Cancer Genome Atlas Ovarian Cancer (NSCLC-Radiomics)
The models featured in this repository uses images from the publically available NSCLC-Radiomics Dataset.
Download the data from TCIA with Descriptive Directory Name download option.
Converting Format
Convert DICOM images and segmentation to NIFTI format using pydicom and pydicom-seg. Run:
user@machine:~/NSCLC-Radiomics-NIFTI$ python convert_segm.py
Segmentations
Images will have one of the following segmentation files:
─ seg-Esophagus.nii.gz
─ seg-GTV-1.nii.gz
─ seg-Heart.nii.gz
─ seg-Lung-Left.nii.gz
─ seg-Lung-Right.nii.gz
─ seg-Spinal-Cord.nii.gz
Requirements
pandas==1.5.0
pydicom==2.3.1
pydicom-seg==0.4.1
SimpleITK==2.2.0
tqdm==4.64.1
Citation
If using this repository, please cite the following works:
Data Citation
Aerts, H. J. W. L., Wee, L., Rios Velazquez, E., Leijenaar, R. T. H., Parmar, C., Grossmann, P.,
Carvalho, S., Bussink, J., Monshouwer, R., Haibe-Kains, B., Rietveld, D., Hoebers, F.,
Rietbergen, M. M., Leemans, C. R., Dekker, A., Quackenbush, J., Gillies, R. J., Lambin, P. (2019).
Data From NSCLC-Radiomics (version 4) [Data set].
The Cancer Imaging Archive.
https://doi.org/10.7937/K9/TCIA.2015.PF0M9REI
Publication Citation
Aerts, H. J. W. L., Velazquez, E. R., Leijenaar, R. T. H., Parmar, C., Grossmann, P., Carvalho, S.,
Bussink, J., Monshouwer, R., Haibe-Kains, B., Rietveld, D., Hoebers, F., Rietbergen, M. M.,
Leemans, C. R., Dekker, A., Quackenbush, J., Gillies, R. J., Lambin, P. (2014, June 3).
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach.
Nature Communications. Nature Publishing Group.
https://doi.org/10.1038/ncomms5006 (link)
TCIA Citation
Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M,
Tarbox L, Prior F.
The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository,
Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057.
https://doi.org/10.1007/s10278-013-9622-7