-We wanted to make an applied AI project to make healthcare tasks simpler and easier.

What it does

-This app segments brain tumours/masses from MRI images.

How we built it

-This app was built using Flask and Pytorch implementing a UNet model.

Challenges we ran into

-We faced challenges in integrating the Pytorch model into the Flask webapp and creating a smooth user interface.

Accomplishments that we're proud of

-Our final app was polished and aesthetically appealing, and also featured fast, real-time inferencing.

What we learned

-We learned how to build and train a computer vision segmentation model for an applied task and integrate it into a simple webapp for deployment.

What's next for Brain Tumour Segmentation App

-We would like to improve this app using more advanced segmentation architectures such as SLSDeep and SegCaps.

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