Blood Cell Diagnostics is a comprehensive AI-powered medical imaging platform designed to classify blood cell images with high accuracy. The system processes 17,000+ images across 8 different blood cell classes, enabling rapid and accurate diagnosis. Built with a custom PyTorch CNN architecture, the platform features a Flask web application with Docker deployment for seamless production use.
Project Overview
Dataset / Input Data
Dataset Name / Source
Blood Cell Image Dataset
Format
Images (PNG/JPG)
Size / Info
17,000+ images across 8 classes
Model / Approach
Algorithm / Model
Custom Convolutional Neural Network (CNN)
Tools / Frameworks
Tech Stack
Python
PyTorch
OpenCV
Flask
Docker
HTML/CSS/JS
Results / Output
Performance Metrics
Accuracy
95%+
Classes
8
Dataset Size
17K+ images
Highlights / Improvements
- Achieved 95%+ accuracy on blood cell classification
- Custom CNN architecture optimized for medical imaging
- Production-ready Flask web application
- Docker containerization for easy deployment
- Real-time image processing capabilities
