A Novel Approach for Calculation of Angles and Curvatures of Human Spine using CT Images Row Data

Spinal deformities are generally associated with lumbar and cervical chronic pain and additionally they disturb the health. In these deformities, lumbar spinal curvature undergone changes in three dimensional space and in most cases, they cause reduction of lung capacities, breathing problems and negative effects on cardiovascular system. In critical deformity cases, in order to correct the deformity and prevent its progression, surgeons determine to perform posterior spinal fusion. As a result, they need to extract some important clinical parameters of spine such as Cobb angle, sagittal and coronal balance, spinal curvature, vertebraes angles and their rotations. In this study, edited tomographic images in MIMICS, were used to prepare a three dimensional model of the spine. Then by using curve fitting techniques and different clustering methods such as self-organization nueral network, k-means and hierarchical method, vertebras were separated and important geometrical data such as curvature of the spine and vertebras angle were obtained. In addition, through implementation of certain algorithms, other clinical features of each vertebra, including minimum and maximum height, length and width of the vertebral body and the relative displacement of vertebras were calculated automatically. In order to validate the proposed methods, measures and angles; derived values obtained automatically at each stage, were again calculated manually in MIMICS. Automatic values were verified by being compared with these manual results. In conclusion the reliability, accuracy and performance of the proposed automatic algorithms were demonstrated.