Brain Tumor Detection System with MRI Using Deep Learning

Authors:

P. BINDHU PRIYA ¹, GURUGUBELLI KIRAN KUMAR ²

¹ Assistant Professor, ² MCA Final Semester, Master of Computer Applications,

Sanketika Vidya Parishad Engineering College,

Vishakhapatnam, Andhra Pradesh, India

bindupriya911@gmail.com,gkirankumar14321@gmail.com

ABSTRACT

Brain tumors are one of the most critical health conditions affecting millions of people worldwide. A brain tumor occurs when abnormal cells grow uncontrollably inside the brain. Early detection of brain tumors is extremely important because delayed diagnosis can lead to severe complications and even death. Traditionally, brain tumor detection is performed manually by radiologists using MRI scans. Although MRI imaging provides detailed visualization of the brain, analyzing a large number of MRI images manually is time-consuming, complex, and susceptible to human errors.

The proposed project titled “BRAIN Tumor Detection System with MRI using Deep Learning” aims to develop an intelligent web-based application capable of automatically detecting brain tumors from MRI images. The system uses a trained CNN model to classify MRI scans into different tumor categories such as Glioma, Meningioma, Pituitary Tumor, and No Tumor. The application provides a user-friendly interface where users can upload MRI images and receive instant diagnostic results along with prediction confidence levels.

Artificial Intelligence (AI),Deep Learning, Machine Learning, Convolutional Neural Network (CNN),Brain Tumor Detection, MRI Scan Analysis, Medical Image Processing, Tumor Classification, Flask Framework, Python Programming, TensorFlow, Keras, NumPy, OpenCV, Image Preprocessing, Neural Networks, Healthcare Technology, Automated Diagnosis, Bootstrap, HTML, CSS, JavaScript, Web-Based Application, Image Normalization, Dataset Training, Tumor Prediction, Glioma Detection, Pituitary Tumor Detection, Meningioma Detection, No Tumor Classification, MRI Dataset.