• Ms. V. Sukanya
• Sriharini Margapuri
• Sree Varsha Lambadi

Tumours are a major global health challenge, early detection of these tumours plays a huge role in improving survival rates. Magnetic Resonance Imaging (MRI) is commonly used for diagnosis of tumours by medical professionals. Deep learning, particularly CNNs, has shown promise in automating tumor detection with high accuracy. This research aims to develop a CNN-based system capable of detecting tumours in various parts of the body - organs like brain, lung, breast and kidney. GradCAM and Contour Mapping are employed to visualise and highlight the predicted area. Additionally, the system is deployed on Streamlit to provide a user-friendly interface for real-time clinical use

TUMOUR DETECTION MODEL USING CNN AND Grad-CAM

"TUMOUR DETECTION MODEL USING CNN AND Grad-CAM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.18-28, May-2025, Available :http://www.jetir.org/papers/JETIRGV06005.pdf

"TUMOUR DETECTION MODEL USING CNN AND Grad-CAM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. pp18-28, May-2025, Available at : http://www.jetir.org/papers/JETIRGV06005.pdf