25,000 histopathological images categorized into 5 distinct classes representing lung and colon tissues. The collection includes both malignant samples and healthy control images for comparative medical imaging analysis.
Use Cases
- Train a convolutional neural network to classify tissue as benign or malignant based on the 5 provided class labels
- Develop automated diagnostic tools for lung cancer detection using the histopathological image features
- Perform comparative morphological analysis between healthy colon tissue and colon cancer samples
Strengths
- 25,000 total high-resolution histopathological images
- 5 specific classes covering lung cancer, colon cancer, and healthy tissue samples
- Uniform distribution with 5,000 images per category