NeuralPath AI - Brain Pathology Detection

NeuralPath AI is a modern, production-ready full-stack web application designed for brain MRI pathology detection using deep learning.

Features

• Pathology Classification: Deep learning based classification for Glioma, Meningioma, and Pituitary tumors.
• Accuracy Metrics: Detailed confidence scoring and softmax probability distributions.
• Batch Processing: Upload up to 20 MRI scans at once with real-time processing status.
• Result History: Local storage based scan history for easy retrieval and comparison.
• Medlens AI Insights: Integration with Groq's Llama-3.1 to generate clinical insights from the model's prediction.
• Dynamic Neural Visualization: Interactive, dynamic 3D neural network representation using Three.js.
• Research Focused UI: Clean interface built with Next.js 15, Shadcn UI, and Framer Motion for demonstrating model performance.

Tech Stack

• Frontend: Next.js 15, Tailwind CSS, shadcn/ui, Framer Motion, Three.js (@react-three/fiber)
• Backend: FastAPI, TensorFlow/Keras, Langchain (Groq Llama-3.1)
• Deployment: Vercel (Frontend), Render (Backend).

Project Structure

• /frontend: Next.js 15 web application.
• /backend: FastAPI inference server & LLM integration.
• /model: ML model weights and pipeline logic.

Quick Start (Local Development)

1. Clone & Setup Environment Variables

git clone https://github.com/En1gma1708/NeuralPath-AI.git
cd NeuralPath-AI

• Copy frontend/.env.example to frontend/.env.local and add your Clerk keys.
• Copy backend/.env.example to backend/.env and add your Groq API key.

2. Start the Backend (FastAPI)

cd backend
python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`
pip install -r requirements.txt
uvicorn main:app --reload

3. Start the Frontend (Next.js)

cd frontend
npm install
npm run dev

Open http://localhost:3000 to view the application.

---

Developed as a Deep Learning Research Project for Brain Pathology Detection.