Lung Cancer Detection - Dataset.zip - Paarth Kapur (20788706) (2025)
This dataset comprises medical images categorized into four distinct classes: Adenocarcinoma, Large Cell Carcinoma, Squamous Cell Carcinoma, and Normal. The dataset includes a total of 1,000 images, with 338 images labeled as Adenocarcinoma, 187 as Large Cell Carcinoma, 260 as Squamous Cell Carcinoma, and 215 as Normal. The images are primarily in PNG format (988 images) with a small fraction in JPG format (12 images). The average image dimensions are 258 pixels in height and 356 pixels in width. The dataset is structured into three subsets: training, validation, and test sets, ensuring proper evaluation and model generalization. Additionally, a separate category, referred to as "bad images," stores non-readable or corrupted images that are unsuitable for processing. The dataset provides a valuable resource for developing and evaluating deep learning models for lung cancer detection and classification.