Pancreatic Cancer Detection System Using Convolution Neural Network

Pancreatic cancer is one of the most lethal forms of cancer due to its late detection and aggressive progression. This study proposes a deep learning-based detection system utilizing a Convolutional Neural Network (CNN) to identify pancreatic cancer from medical imaging data, such as CT and MRI scans. The model is trained on a labeled dataset to automatically extract and learn hierarchical features distinguishing malignant from healthy pancreatic tissue. Through rigorous evaluation, the CNN demonstrates promising accuracy and sensitivity, highlighting its potential as a supportive diagnostic tool. The proposed system aims to aid radiologists in early detection, reduce diagnostic errors, and improve overall clinical outcomes.