• DURGA PRASAD RAJULAPATI
• Yenduri Veera Venkata Naga Bhargavi
• Gudise .Pavani
• Mr.Seepani .Sai Kiran
• Angalakurthi .Akash ,Thokala Chaitanya

Lumbar diseases, such as herniated discs, spinal stenosis, and spondylosis, cause severe back pain and mobility issues. This study presents a Hybrid Convolutional Neural Network (CNN) combined with K-Means clustering for accurate classification of into four categories: Healthy, Herniated Disk, Spinal Stenosis, and Spondylosis. The system then suggests making precise decisions. treatment options. The proposed method improves accuracy, reduces misdiagnosis, and assists doctors in lumbar diseases using MRI scans. The process involves pre processing MRI images, segmenting the relevant regions, extracting features, and classifying the images.

"ENHANCING LUMBAR DISEASE ACCURACY IN CLASSIFICATION WITH CNN AND IMAGE SEGMENTATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.i73-i80, March-2025, Available :http://www.jetir.org/papers/JETIR2503809.pdf

"ENHANCING LUMBAR DISEASE ACCURACY IN CLASSIFICATION WITH CNN AND IMAGE SEGMENTATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppi73-i80, March-2025, Available at : http://www.jetir.org/papers/JETIR2503809.pdf