Inspiration
The main driving force behind this project development was the never stopping habit of Learning. We thought of helping patient know a predicted result for the Brain Tumor test report
What it does
A Web App for Brain Tumor detection using MRI Scan with an easy UI.
How we built it
We made a machine learning model which classifies the images using Convolutional Neural Network CNN.
By using a dataset from Kaggle, which comprises of both images with tumor and without tumor then by splitting the dataset into training and testing sets with a ration of 80%:20%.
At the end, we used Sequential Model by Keras to build our CNN model, and its respective layers to train the model The Model gives the result with an accuracy level of 90%.
Challenges we ran into
The irritating and head eating bugs are something that almost every developer faces. This was something that we too struggled a lot tackling with, but in the end we were able to smash all the bugs out of our codes 🔥🔥🔥
Accomplishments that we're proud of
We are very proud that we were able to complete the whole project in the stipulated time. We hope this application can really help the people in need and provide them some peace of mind.
What we learned
We got to learn about the CNN model more deeply. We also learned new implementations in Flask.
What's next for Brain Tumor Predictor
We plan to further Add more types of Deadly Diseases' Detection by expanding our Web App and enhancing the overall user experience & ease of access.
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