Computed tomography image analyzer: 3D reconstruction and segmentation applying active contour models  snakes
Many diagnostic and therapeutic procedures depend on medical images. In order to overcome imperfections of the obtained images, which are due to the acquisition process, and to extract new information from the available images, many techniques have been developed. In this study, a new method of image segmentation and 3D reconstruction based on active contour models (snakes) was applied in analyzing computed tomography (CT) images in patients with acute head trauma. Using this method, lesion to brain (LBR) and ventricle to brain ratio (VBR) parameters, as well as 3D reconstruction of traumatic lesion, was obtained accurately. In our study group, 215 patients (mean age 42.423.5 years, 138/215 (64.2%) males) were included. Among them, 72 (33.5%) did not survive during hospitalisation in the Emergency Department. LBR correlated with the Glasgow Coma Score and the intrahospital outcome (r=?0.457 and r=0.515, respectively). Besides, non-survivors had greater LTB values (0.0420.034) than survivors (0.0050.011). However, VBR did not correlate with these clinical parameters. In addition, LBR was significantly higher in the patients with other pathologic CT findings. The proposed methodology, based on extracting maximum information from available CT scans, could be a basis for further medical decision making in patients with acute head trauma.
computed tomography 3d reconstruction segmentation medical decision making image analysis