• V. LAKSHMI PRASANNA KUMARI
• Dr. P. SIVA KRISHNA
• D.V SATEESH KALADHAR REDDY

A brain tumor is a growth of abnormal cells in the brain or near it. Identifying brain tumor lately may cause serious issue to the person. So, to identify it in the initial stages we use convolutional neural networks. Convolutional Neural Networks (CNNs) is a popular and promising approach for medical image analysis. These networks can effectively learn features from medical images and provide accurate diagnoses for brain tumor. The general process for using CNNs for brain tumor detection and classification involves data acquisition, data preprocessing, data augmentation, model selection, model training, model evaluation and model deployment. They show promising solution for detecting brain tumors as they are more accurate and efficient in medical diagnosis. Through this, the types of brain tumor can be identified that can reduce the risk of people and can increase the chances of life expectancy, when started diagnosing in early stages. As these networks continue to evolve, they are expected to become an even more important tool for medical professionals in the future.

"DETECTION OF BRAIN TUMOR USING NEURAL NETWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 8, page no.e17-e24, August-2025, Available :http://www.jetir.org/papers/JETIR2508403.pdf

"DETECTION OF BRAIN TUMOR USING NEURAL NETWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 8, page no. ppe17-e24, August-2025, Available at : http://www.jetir.org/papers/JETIR2508403.pdf