• Pati Sandeep Reddy
• M Rithwik Reddy
• Roshan Mahapatra

The proposed system is designed to automate detection and classification of lumbar spine diseases using deep learning and medical imaging techniques. By leveraging Convolutional Neural Networks (CNNs), the system analyzes MRI and X-ray images to identify abnormalities such as herniated discs, spondylosis, and degenerative disc disease. This approach enhances early diagnosis, reduces human error, and assists radiologists in making more accurate clinical decisions. The system integrates image preprocessing, feature extraction, and classification models to provide a user-friendly interface for medical professionals. Key features include automated image processing, real-time disease classification, and detailed statistical analysis for better medical insights.

Deep Learning,Convolutional Neural Networks,Lumbar Spine,Artificial Intelligence,Medical Image Preprocessing

"LUMBAR SPINE DISEASE DETECTION AND ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.i347-i353, May-2025, Available :http://www.jetir.org/papers/JETIR2505937.pdf

"LUMBAR SPINE DISEASE DETECTION AND ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppi347-i353, May-2025, Available at : http://www.jetir.org/papers/JETIR2505937.pdf