Knee Osteoarthritis Classification [224*224]

The Multi-Class Knee Osteoporosis X-Ray Dataset is a high-quality collection of knee X-ray images, sourced from Kaggle  and Mendeley Data. This dataset is designed for advanced machine learning and deep learning applications in medical imaging, specifically for osteoporosis detection.

Key Features

✅ Extensive Image Collection – A total of 3,600 knee X-ray images after augmentation, categorized into Normal, Osteopenia, and Osteoporosis.
✅ Multi-Source Data – Integrated from multiple reliable databases, including the Knee X-ray Osteoporosis Database and the Digital Knee X-ray Images Dataset.
✅ Balanced Class Distribution – Class imbalance addressed with data augmentation (flips, rotations) to ensure equal representation.
✅ High-Resolution Medical Imaging – Quality X-ray scans suitable for deep learning, computer vision, and AI-powered diagnosis.
✅ Pre-Split Dataset – Ready-to-use training (70%), validation (20%), and testing (10%) sets for seamless AI model training.
✅ Optimized for AI & Machine Learning – Ideal for CNN-based classification, medical image analysis, and osteoporosis detection.
✅ Biomedical & Radiology Applications – Supports computer-aided diagnosis (CAD) and medical research on osteoporosis progression.

Applications

This dataset is ideal for: 🔹 Deep learning & AI-based medical image classification
🔹 Computer-aided diagnosis (CAD) for osteoporosis detection
🔹 Biomedical research in bone health & radiology
🔹 Development of CNN-based diagnostic tools for orthopedic conditions
🔹 Enhancing AI-driven healthcare solutions