AI-Powered Brain Tumor Classification

Automating early tumor detection with deep learning.

Problem Statement: Traditional MRI analysis is time-consuming and prone to human error. This AI-based classification system automates tumor detection with high precision.

Brain Tumor Classification AI

Milestones Achieved

Multi-Class Tumor Classification
Detects Glioma, Meningioma, Pituitary Tumors, and Non-Tumor cases.
Deep Learning Integration
Uses Xception CNN model for feature extraction.
Enhanced Model Performance
Fine-tuned for increased precision and recall.
Real-Time Predictions
Provides instant MRI image classification via a Gradio-based interface.
Robust Data Augmentation
Provides an interactive and seamless user experience.

Techniques Used

Transfer Learning: Utilizes Xception pretrained on ImageNet for feature extraction.

Custom Deep Learning Model: Implements fully connected layers with dropout regularization.

Data Augmentation: Enhances training with brightness adjustments and rescaling.

Fine-Tuning Strategy: Unfreezes top layers of Xception for improved adaptability.

Gradio Web App: Provides an interactive interface for real-time classification.

Empower Medical Diagnostics with AI

Accelerate brain tumor detection with deep learning technology.

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