Brain Tumor Classification

Overview of random images and their predicted diagnosis
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Accuracy Score
Accuracy Matrix
Classification Table
Code
Code

Inspiration:

We were inspired to create our Brain Tumor Classification model because we wanted to use technology to make a positive impact on people's lives. We learned that early detection of brain tumors is crucial for better treatment outcomes, and we wanted to develop a tool that could help doctors diagnose tumors more accurately and quickly.

What it does:

Our Brain Tumor Classification model can analyze medical images of the brain, specifically MRIs, and determine whether a certain type of tumor (pituitary, glioma, and meningioma) is present or not. It uses algorithms to make these predictions, which can assist doctors in making more informed decisions about a patient's diagnosis.

How we built it:

We built our Brain Tumor Classification model by sourcing a large dataset of brain images with and without tumors, labeled by type. Then, we used python and data libraries like opencv, numpy, and matplotlib to teach our model to recognize the differences between them. We spent many hours training and testing the model to make sure it was as accurate as possible.

Challenges we ran into:

One of the biggest challenges we faced was finding a large and diverse dataset to train our model effectively. We also had to overcome technical issues some of which we are still trying to solve and improve. We would like to ensure that our model is reliable enough for medical use.

Accomplishments that we're proud of:

We're proud that our Brain Tumor Classification model achieved high accuracy in detecting brain tumors. It can help doctors make quicker diagnoses and improve patient outcomes. We're also proud of our teamwork and dedication in overcoming challenges throughout the project.

What we learned:

Throughout this hackathon project, we learned about the importance of data, algorithms, and teamwork in building machine learning models. We gained a deeper understanding of how AI can be used for medical purposes and its potential to save lives.

What's next for Brain Tumor Classification:

In the future, we plan to refine our model further and make it accessible to healthcare providers worldwide. We aim to collaborate with medical professionals to ensure it meets their needs to explore the possibility of extending the model’s reach to detect more types of brain tumors. Ultimately, we hope to contribute to better healthcare through the power of AI.