Image data is available in DICOM format. Segmentation data is available in .nii format. Labels are available in .csv format. The first column is subject identification. The second column is survival class. Subsequent columns are computed image features which are described in the following publications.
Hawkins, Samuel H., John N. Korecki, Yoganand Balagurunathan, Yuhua Gu, Virendra Kumar, Satrajit Basu, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, and Robert J. Gillies. "Predicting Outcomes of Nonsmall Cell Lung Cancer using CT Image Features." IEEE Access 2 (2014): 1418-1426. DOI: 10.1109/ACCESS.2014.2373335
Paul, Rahul, Samuel H. Hawkins, Yoganand Balagurunathan, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, and Dmitry B. Goldgof. "Deep Feature Transfer Learning in Combination with Traditional Features Predicts Survival Among Patients with Lung Adenocarcinoma." Tomography: a journal for imaging research 2, no. 4 (2016): 388. DOI:10.18383/j.tom.2016.00211
Note: This data is restricted against commercial use. Please contact firstname.lastname@example.org with any questions on usage.
- DICOM Image Data: (
- Click the Download button above to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever.
- Segmentations (NIFTI)
- Patient Survival & Image Features