Spinal Column Diagnosis in Cervical Vertebrae Interface Using Image Spectral Techniques

With the time, as there is advancement in medical technology, there is also a huge increment in number of physical disabilities and diseases. Among them some are curable and some aren't. Low back pain & sub-acute pain growing simultaneously. Ignorance of such pain becomes chronic disease which not only affect our spine, but also affect our work. Cervical traction is most preferred treatment for cervical spine disabilities in intervertebral disc, the vertebrae, the ligaments, and the facet joints but its effectiveness as a part of physical therapy is a matter of discussion. First step for spinal column diagnosis is vertebra detection. Due to presence of skull bone in C-spine region this task becomes more difficult as X-ray images considered are noisy low contrast images. In this paper an automatic approach is proposed for calculating intervertebral posterior height and based on the distance between different vertebrae traction force at C-spine region is calculated. The Proposed method consists of following steps: 1) Vertebra detection 2) Intervertebral posterior height calculation 3) calculating traction weight. Data of 17 volunteers and X-ray Image data of 12 cases are taken to validate our approach by using a total of 60 cervical vertebrae. The objective is to find ROI and localize cervical spine centers. Thus, an automatic approach is proposed which gives generalization to traction therapy. Image analysis of C-spine is achieved with an accuracy of 98 %. Image characterized as normal or abnormal cervical image; also, exact traction weight is calculated using physics behind traction. 8% of the body weight will be the ideal weight to start traction with minimal side effect and highest therapeutic efficacy. Therefore, clinicians could adopt this weight as minimum weight in managing neck disorder requiring traction and goes up to the weight as calculated by proposed algorithm.