Brain Vision AI

Upload your brain CT scans to Brain Vision AI, and our AI analyzes them with over 99% accuracy to determine if they're cancerous or non-cancerous. Fast, reliable early detection from home.

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Inspiration

The growing need for early brain cancer detection inspired us to create a user-friendly, accessible solution. We aimed to leverage AI technology to offer quick, accurate diagnoses, potentially saving lives.

What it Does

Brain Vision AI allows users to upload CT scan images of their brains. Our advanced AI algorithm analyzes the images and determines whether they are cancerous or non-cancerous with a 99.04% accuracy rate.

How We Built It

We utilized Python, TensorFlow, Keras, and OpenCV (cv2) to develop our AI model. The model was trained on a vast dataset of Brain CT scans to ensure high accuracy and reliability. Our platform is hosted on a robust cloud infrastructure, enabling scalability, accessibility, and secure data handling.

Challenges We Ran Into

One of the main challenges we faced was obtaining a comprehensive dataset of Brain CT scans for training, specifically, for differentiating between the various types of Brain cancer. Additionally, identifying where the model was failing and retraining it to improve accuracy was also a huge issue. However, through perseverance and hard work, we were able to power through these problems.

Accomplishments That We're Proud Of

We're extremely proud of achieving an above 99% accuracy rate. Initially, our model had a rather poor accuracy; however, by identifying its weaknesses and making necessary adjustments, we achieved an almost 8% increase.

What We Learned

Throughout this project, we learned the importance of data quality and quantity in training accurate AI models. We gained insights into the complexities of medical imaging and the need for rigorous testing and validation.

What's Next for Brain Vision AI

In the short term, we plan to further improve our model's accuracy and expand its capabilities to detect other brain conditions. Additionally, we aim to integrate with small-time healthcare providers. Our long-term goal is to create a comprehensive diagnostic tool that can be used globally to save lives.

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