The goal of this project is to develop a deep learning model for the classification of chest cancer using PyTorch and EfficientNet
Images are not in dcm format, the images are in jpg or png to fit the model Data contain 3 chest cancer types which are Adenocarcinoma,Large cell carcinoma, Squamous cell carcinoma, and 1 folder for the normal cell Data folder is the main folder that contain all the step folders inside Data folder are train, valid, and test
training set is 70%
testing set is 20%
validation set is 10%
Adenocarcinoma Adenocarcinoma of the lung: Lung adenocarcinoma is the most common form of lung cancer accounting for 30 percent of all cases overall and about 40 percent of all non-small cell lung cancer occurrences. Adenocarcinomas are found in several common cancers, including breast, prostate and colorectal. Adenocarcinomas of the lung are found in the outer region of the lung in glands that secrete mucus and help us breathe. Symptoms include coughing, hoarseness, weight loss and weakness.
Large cell carcinoma Large-cell undifferentiated carcinoma: Large-cell undifferentiated carcinoma lung cancer grows and spreads quickly and can be found anywhere in the lung. This type of lung cancer usually accounts for 10 to 15 percent of all cases of NSCLC. Large-cell undifferentiated carcinoma tends to grow and spread quickly.
Squamous cell carcinoma Squamous cell: This type of lung cancer is found centrally in the lung, where the larger bronchi join the trachea to the lung, or in one of the main airway branches. Squamous cell lung cancer is responsible for about 30 percent of all non-small cell lung cancers, and is generally linked to smoking.