dorsar/lung-cancer-detection
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in Data Studio
Lung Cancer CT Scan Dataset
Dataset Description
This dataset contains CT scan images for lung cancer detection and classification. It includes images of four different categories: adenocarcinoma, large cell carcinoma, squamous cell carcinoma, and normal (non-cancerous) lung tissue.
Classes
- Adenocarcinoma
- Large Cell Carcinoma
- Normal (non-cancerous)
- Squamous Cell Carcinoma
Dataset Statistics
- Total number of images: 315
- Number of classes: 4
- Class distribution:
- Adenocarcinoma: 120 images
- Large Cell Carcinoma: 51 images
- Normal: 54 images
- Squamous Cell Carcinoma: 90 images
Usage
This dataset is suitable for training and evaluating machine learning models for lung cancer detection and classification. It can be used for both binary classification (cancerous vs. non-cancerous) and multi-class classification (specific cancer types).
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Size of downloaded dataset files:
98.5 MB
Size of the auto-converted Parquet files:
78.2 MB
Number of rows:
767
Models trained or fine-tuned on dorsar/lung-cancer