SCOLIO-SEE · 3D-IMAGE PROCESSING SYSTEM FOR HELPING PHYSICIANS IN THE DIAGNOSIS AND MONITORING OF SCOLIOSIS

Scoliosis is a three-dimensional (3D) deformity of the human spinal column and ribcage, caused by lateral curvature deviating from the midline and provoking acute pain, stomach and respiratory problems. This internal deformity is reflected in the external shape of the back; treatment aims at improving the health and the aesthetics of the patients.From the health point of view, the golden standard for diagnosing and monitoring scoliosis is the Cobb angle which refers to the internal curvature of the spine (by means of radiographs); from the external or aesthetic point of view there are a well-known variety of measurements and surface indices that quantify the severity of scoliosis.Many studies show that it is not possible to predict the Cobb angle by means of previous X-rays, nor to infer a concrete value of the Cobb angle by means only of surface indices, because radiograph and surface topography measurements are not redundant, but complementary. Nevertheless, although it is not possible to eliminate X-ray radiographs, their number can be reduced to a large extent by an adequate combination of surface and radiographic measurements; different studies show that the reduction in the number of radiographs is very important because patients with scoliosis have higher risk of cancer due to repeated radiation exposure.SCOLIO-SEE is a software and hardware system that, for the first time, will combine the data obtained by both radiographic and surface topography techniques; this matching between internal and external deformation will permit monitoring spine curvature evolution after treatment by analyzing only surface changes, reducing the number of radiographs needed to a level that it is not harmful for the patients. Additionally, a software module will be developed to compare the 3D images taken for each individual patient in two successive visits, to show the 3D-changes occurred in the whole back surface occurred in this time interval.