Early Cancer Detection from MRI Dataset Using a Deep Learning Model

This project explores early cancer detection using MRI images processed through a convolutional neural network (CNN). The goal is to improve diagnostic accuracy and reduce detection time through automated image classification.

“This project can be expanded to support multiple cancer types and integrated into clinical workflows.”

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The system is trained on publicly available MRI datasets to distinguish between normal and cancerous tissue. Various deep learning architectures were tested, with a custom CNN model delivering the highest performance. The model achieved high sensitivity and specificity, indicating its potential as a supportive tool for radiologists.