The project "Lung Cancer Detection Using CNN" focuses on developing a deep learning-based approach for early and accurate detection of lung cancer using medical imaging data such as CT scans or X-rays. Early detection is critical for improving survival rates and treatment outcomes.
The main types of lung cancer are: non-small cell lung cancer and (NSCLC) and small cell lung cancer (SCLC).
About 10% to 15% of all lung cancers are SCLC.
About 80% to 85% of lung cancers are NSCLC. The main subtypes of NSCLC are adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. These subtypes, which start from different types of lung cells, are grouped together as NSCLC because their treatment and prognoses (outlooks) are often similar.
Lung adenocarcinoma starts in cells in the lung that make mucus, called epithelial cells. Epithelial cells line the surface of the lungs. Adenocarcinoma is the most common type of non-small cell lung cancer
Squamous cell carcinoma starts in squamous cells, which are flat cells that line the inside of the airways in the lungs. They are often linked to a history of smoking and tend to be found in the central part of the lungs, near a main airway (bronchus).
Large cell carcinoma can appear in any part of the lung. It tends to grow and spread quickly, which can make it harder to treat. A subtype of large cell carcinoma, known as large cell neuroendocrine carcinoma (LCNEC), is a fast-growing cancer that is very similar to small cell lung cancer.
We collected data from Kaggle The dataset contains CT-scan of NON-SMALL CELL LUNG CANCER *Adenocarcinoma *Large cell carcinoma *Squamous cell carcinoma *Normal
dataset link :- https://www.kaggle.com/datasets/mohamedhanyyy/chest-ctscan-images
Here, the Inseption V3 model is more precise.
