An automatic detection method of spinal deformity from moire topographic images employing asymmetric degree of shoulder and waistline

Spinal deformity is one of serious diseases, mainly suffered by teenagers during their growth stage. To detect the spinal deformity in early stage, orthopedists have traditionally performed a painless examination called a forward bending test or moire topographic image test in mass screening of school. It is, however, inspection base on the forward bending method takes much time and moire images, and visual examination also require a large amount of moire images because they are collected from elementary as well as junior high schools. This causes exhaustion of doctors and therefore leads to misjudgment. Therefore realization of automatic spinal deformity detection based on the moire images has long been desired among orthopedists. In this paper, we propose a method for automatic detection of spinal deformity from moire topographic images by using a new asymmetric feature which is obtained by using statistical features between left- and right hand side shoulder and waist lines. We classified an unknown moire image employing linear discriminant function. The proposed technique is applied to 1200 real moire topographic images. By the employment of the two asymmetric features, 66% of unknown moire images were successfully classified in the performed experiment. Some experimental results are shown along with discussions.