Quantification of morphological parameters that describe the spine and pelvis, such as the coronal vertebral inclination (CVI), sagittal vertebral inclination (SVI), axial vertebral rotation (AVR) or pelvic incidence (PI), is valuable for ascertaining diagnosis, determining prognosis, and guiding treatment decisions related to spinal and pelvic deformities. This book concentrates on the evaluation of spinal and pelvic parameters from three-dimensional (3D) medical images. Spinal curvature, vertebral rotation and sagittal pelvic alignment were quantitatively evaluated from computed tomography (CT) and magnetic resonance (MR) images by existing and novel manual and computerized measurement methods, and the results were analyzed in terms of the variability introduced by methods and observers. Although manual measurements are still widely used, computerized measurements that apply image processing and analysis techniques are considerably faster and less observer-dependent. The reproducibility and reliability are higher when parameters are evaluated from 3D than two-dimensional images, but 3D images are more demanding in terms of availability, manipulation and interpretation. However, 3D images help clinicians making more accurate diagnosis and planning more effective treatment strategies for spinal and pelvic deformities, while methods for computer-assisted diagnosis are constantly being developed to aid in the interpretation of the increasing amount of medical image information.
F.03 Increased qualifications of the research and development staff
COBISS.SI-ID: 256118016Among the techniques for analysis of three-dimensional (3D) spine images, segmentation does not only improve the visualization of vertebrae, but also provides means for reliable and accurate measurement of vertebral deformations in their natural 3D space. The observer’s influence from the segmentation process can be excluded with automatic initialization that provides an estimation of the size, location and position of the vertebra in the image. This thesis concentrates on the design, development and validation of methods for accurate and reliable analysis of vertebral body deformations that are based on automated detection and segmentation of the vertebral body in 3D medical images. To verify the clinical applicability, the methods are compared with clinically established methods used for the evaluation of vertebral deformations in two-dimensional (2D) medical images.
D.09 Tutoring for postgraduate students
COBISS.SI-ID: 262692096We presented a completely automated algorithm for the detection of spinal centerlines and the centers of vertebral bodies and intervertebral discs in images acquired by computed tomography (CT) and magnetic resonance (MR) imaging. The developed methods are based on the analysis of the geometry of spinal structures and the characteristics of CT and MR images and were evaluated on 29 CT and 13 MR images of lumbar spine. The overall mean distance between the obtained and the ground truth spinal centerlines and centers of vertebral bodies and intervertebral discs were 1.8 +/- 1.1 mm and 2.8 +/- 1.9 mm, respectively, and no considerable differences were detected among the results for CT, T1-weighted MR and T2-weighted MR images. The knowledge of the location of the spinal centerline and the centers of vertebral bodies and intervertebral discs is valuable for the analysis of the spine. The proposed method may therefore be used to initialize the techniques for labelling and segmentation of vertebrae.
D.10 Educational activities
COBISS.SI-ID: 7298388The determination of vertebral and intervertebral disc endoprothesis geometrical parameters of the lumbar spine is important for evaluating the process and outcomes of the treatment after total endoprothesis implantation. The searched geometrical parameters in this work are the angle between vertebral endplates in contact with the disc or endoprothesis, the angle between endoprothesis plates and the normalized distance between the central points of vertebral endplates. We determined the geometrical parameters on radiographic images of lumbar spine using manual and computerized methods. The results are presented together with statistical analysis.
D.10 Educational activities
COBISS.SI-ID: 8186708