Chest Cancer CT Image Dataset for Deep Learning Classification

This dataset contains chest CT images categorized into four clinical classes: Adenocarcinoma (326 images), Large Cell Carcinoma (163 images), Squamous Cell Carcinoma (252 images), and Normal (159 images). All images were collected from a collaborating hospital and represent real clinical cases. No synthetic or artificially generated data was included.

The images were reviewed by a radiologist, an oncologist, and a pulmonary specialist to ensure correct labeling and clinical validity.

All data were fully anonymized by the hospital before being shared with the researcher. No personal or sensitive patient information was accessed or stored at any stage. The dataset consists entirely of secondary anonymized clinical images, and formal ethical approval was not required for this work.

The dataset is intended for research in medical image classification, particularly in lung cancer detection using machine learning and deep learning techniques. All files are organized in a folder named “Data 2” which contains four subfolders corresponding to the four classes.