Neural Network Based Spinal Age Estimation Using Lumbar Spine Magnetic Resonance Images (MRI)

A human spine is a complicated structure of bones, joints, ligaments and muscles which all undergo a process of change with the age. This paper describes the existence of a pattern in degenerative process of human spine. Unveiling this pattern will be helpful in reassuring patients that the results of their scan are not unusual or indicative of any disease. A model based on artificial neural networks was formed with the help different spinal features such as vertebral height, disc height, disc signal and para-spinal muscles etc. These features of the lumbar spine vary with the age. Proposed model puts the degenerative changes of the lumbar spine into the context of a normal ageing process to estimate patient "spinal age". This research work will provide a more concrete view of spinal growth in human being with the help of statistical features. This work will be helpful in drawing a borderline between normal, under and over growth of the human spine with respect to the person's age.