Sharing data for cancer research
Radiomics
Data from: Survival prediction of non-small cell lung cancer patients using radiomics analyses of cone-beam CT images
Radiomics Digital Phantom
Prognostic value of metabolic metrics extracted from baseline positron emission tomography images in non-small cell lung cancer
Download the images using these instructions and this DOI:10.3109/0284186X.2013.812795
BACKGROUND:
Maximum, mean and peak SUV of primary tumor at baseline FDG-PET scans, have often been found predictive for overall survival in non-small cell lung cancer (NSCLC) patients. In this study we further investigated the prognostic power of advanced metabolic metrics derived from intensity volume histograms (IVH) extracted from PET imaging.
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
Human cancers exhibit strong phenotypic differences that can be visualized noninvasively by medical imaging. Radiomics refers to the comprehensive quantification of tumour phenotypes by applying a large number of quantitative image features.