Lung Cancer Images for Classification

The author obtained the CT Scan images dataset from the Cancer Imaging Archive collection; there are two related research on the dataset: LDCT and Projection Image (https://doi.org/10.7937/9NPB-2637) and the Quantitative computed tomographic descriptors associate tumor shape complexity and intratumor heterogeneity with prognosis in lung adenocarcinoma (https://doi.org/10.7937/K9/TCIA.2015.A6V7JIWX). The research combines the series of filters named Multi-stage and deep learning CNN for classification. The 3D lung images would be extracted and filtered out using geometric properties from the dataset on a smaller dimension of 20x20x20 before the training. The intended output is the cancer annotation (as the CNN output) and RADS scores (from the nodule properties).