Brain Tumor Detection : CNN Based Brain Tumor Detection for MRI Scan

Brain Tumor Detection : CNN Based Brain Tumor Detection for MRI Scan

Purva Bhong

purvabhong22@gmail.com

  Computer Science Department MIT-ADT, Pune

Ektaa Rawal

ektaarawal211@gmail.com

Computer Science Department MIT-ADT, Pune

Srushti Dhanawade

srushtidhanawade82003@gmail.com Computer Science Department MIT- ADT, Pune

Saloni Mohite

srmohite2004@gmail.com

Computer Science Department MIT-ADT, Pune

Prof. Chhaya Mhaske   chhaya.mhaske@mituniversiy.edu.in

Computer Science Department MIT-ADT, Pune

ABSTRACT

    The Brain tumor detection and classification are critical for effective treatment of the patient care. This study proposes a Convolutional Neural Network (CNN)-based approach for analyzing brain MRI images to automatically detect and classify brain tumors. The model is trained on a labeled dataset consisting of various tumor types, including glioma, meningioma, and pituitary tumors. Through image preprocessing, data augmentation, and optimized CNN architecture, the system achieves high accuracy and reliability in tumor classification. The results demonstrate the potential of CNNs in supporting radiologists with faster and more accurate diagnoses, paving the way for improved medical imaging solutions.

KEY WORDS
Brain tumor detection, Convolution Neural Network(CNN),

Magnetic Resonance Imaging(MRI), Deep Learning, Medical

Image Analysis