Inspiration The inspiration behind this project came from growing need for early and accurate detection need for early and accurate detection of brain tumor , as timely diagnosis can save lives . i was motivated by how artificial intelligence is transforming healthcare and wanted technique to solve real world medical challenges .
What it does - it does this project automatically detects the presence of brain tumor from MRI images using deep learning models like VGG16 and DNN . it processes the scans , classifies them as tumor or non - tumor , and provides accurate results to assist doctors in faster and more reliable diagnosis .
How we built it - the project is built using MRI image datasets , where the scans are preprocessed and fed into deep learning models like - VGG16 and DNN .using transfer learning and feature extraction , the system classifies classifies images into tumor and non tumor categories , ensuring accurate and efficient brain tumor detection.
Challenges we ran into - the main challenges were handling limited and imbalanced MRI datasets , managing high computational requirements , and ensuring the model generalized well without overfitting .dataset preprocessing , augmentation , and transfer were key strategies to overcomes these issues .
Accomplishments that we're proud of - we successfully built a deep learning model that can detect brain tumor from MRI images with high accuracy . we are proud of achieving reliable result despite limited data , improving model performing using transfer learning , and creating a system that shows real potential to assist in early medical diagnosis.
What we learned - we learned how to preprocess and work with medical imaging data , apply deep learning models like VGG16 and DNN , and use transfer learning to improve accuracy . beyond technical skills , we also understood the importance of clean data , model evaluation and the real world impact of AI in healthcare.
What's next for BRAIN TUMOR DETECTION IN MACHINE LEARNING
Log in or sign up for Devpost to join the conversation.