Automated Lumbar Spine Degeneration Classification: Deep Learning and Web-Based Approach

Abstract

Lumbar Spine Degenerative Classification project focuses on automating the diagnosis of lumbar spine degeneration using advanced image analysis techniques. Traditional methods rely on manual interpretation of MRI scans, which can be time-consuming and inconsistent. To improve accuracy and efficiency, this system processes medical images using specialized computational models. The images undergo pre-processing to enhance quality and ensure uniformity. A structured approach extracts important features from MRI scans for precise classification. Fine-tuning techniques optimize performance for reliable results. The system is designed for real-world use through a web-based interface, allowing easy access for medical professionals. It reduces errors and speeds up the diagnostic process. Future improvements include expanding its capabilities to detect other spinal disorders. This work enhances healthcare accessibility and supports better patient care.