OncoMRI

"Joining Hearts, Defeating Brain Cancer: Together We Rise"

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OncoMRI : The Tumor Teller

Theme :

By combining advanced technology and compassionate care, we aim to improve brain health and create a healthier future with AI-powered solutions.

The existing methods of diagnosing brain tumors through MRI scans often involve time-consuming and error-prone manual analysis by medical professionals. Additionally, there is a need for a secure and privacy-centric approach to handling sensitive patient data during the diagnostic process. The key points of the problem statement are as follows:

MRI scans are currently used to diagnose brain tumors, but this process often involves manual analysis by medical professionals, which can be time-consuming and prone to errors. Additionally, patient data must be handled securely and privately during the diagnostic process. The problem statement can be summarized as follows:

Manual MRI Analysis: Current methods rely heavily on manual analysis, which can cause delays in diagnosis and treatment planning.
Accuracy and Efficiency: Early detection and timely intervention are crucial for patient outcomes and survival rates, so there is a need for a more accurate and efficient tumor identification process.
Lack of Comprehensive Information: Patients often receive limited information about their brain tumor, which can hinder informed decision-making. Providing comprehensive insights is essential for patient empowerment.
Data Privacy Concerns: Patient data, including MRI scans, must be handled securely and not stored for privacy reasons.
Streamlining Appointment Booking: Appointment booking can be cumbersome and inefficient. An integrated system that facilitates seamless scheduling and communication is essential for patient convenience.

Solution: 💡

In light of these challenges, OncoMRI aims to create an intelligent and privacy-focused solution that revolutionizes brain tumor diagnosis using AI-driven analysis. By leveraging the power of Azure Custom Vision, the application seeks to empower patients with comprehensive tumor insights and personalized treatment recommendations, ultimately contributing to improved patient outcomes and enhanced brain health care.

OncoMRI is an innovative medical software application designed to revolutionize brain tumor diagnosis through AI-driven MRI analysis.
Leveraging Azure Custom Vision's pre-trained machine learning model, the app accurately identifies Meningioma, Glioma, and Pituitary tumors from uploaded MRI scans.
The platform ensures privacy by not storing any user data or MRI scans, safeguarding sensitive medical information through Streamlit.
With a user-friendly interface built using Streamlit, patients can easily upload MRI scans and receive rapid and precise tumor identification results.
Detailed insights about the detected tumor, including its characteristics, causes, effects, and potential treatments, are provided to enable informed decision-making.
Personalized treatment recommendations based on the tumor type and stage empower patients to make the best healthcare choices.
OncoMRI streamlines appointment booking with specialized doctors through its integrated Azure Logic App, facilitating seamless communication.
The app's focus on data privacy, accuracy, and efficiency contributes to early detection and timely intervention, improving patient outcomes and brain health care.

Tech Stack:

The following tech stacks have been used to create the application and deploy it.

Python to build the application.
Streamlit to create a responsive web application along with widgets.
Streamlit Community Cloud to deploy the web application for anyone across the globe to access it.
Microsoft Azure AI Custom Vision to get a computer vision model trained using our dataset and use it to predict the tumor type with the patient's MRI scan.
Microsoft Azure Logic App to send emails to the patient, doctor on appointment booking.
GitHub to host the source code, use the version control (collaboration history), pull requests and GitHub collaboration features to build efficiently with the teammates. It helps a lot to understand the changes and go back and forth if required to complete the software.