🧠 Cancer-Detection-CNN This project implements Convolutional Neural Networks (CNNs) to detect and classify lung cancer tumors and skin cancer (melanoma) from medical images. It leverages deep learning techniques to assist in early diagnosis by analyzing CT scans for lung tumors and dermatoscopic images for skin lesions.
🚀 Features CNN-based binary and multi-class classification for:
Lung cancer detection from CT scan images
Melanoma vs. benign lesion detection from skin images
Preprocessing pipeline including resizing, normalization, and augmentation
Training with real-world datasets (e.g., LIDC-IDRI, ISIC)
Accuracy and performance metrics (confusion matrix, ROC-AUC, etc.)
Easily extensible to other types of cancers
🛠️ Tech Stack Python
TensorFlow / Keras
OpenCV
NumPy / Pandas / Matplotlib
📊 Results Achieved high validation accuracy on both datasets, demonstrating the model's potential in aiding medical professionals with early detection.