Abstract
Rigid registration of bone structures in stacks of CT images can be improved by using a binary segmentation mask for the registration compared to using the segmented grey values directly. Three criteria are applied to the different reference and template datasets in order to quantify registration results. For all three criteria a statistically significant superiority of the technique using the binary segmentation masks is demonstrated. First results for a multimodal registration of a μCT with μMR dataset also show better results if binary segmentation masks are used for the registration.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hajnal JV, Hill DLG, Hawkes DJ, editors. Medical Image Registration. CRC; 2001.
Wang L, Greenspan M, Ellis R. Validation of bone segmentation and improved 3D registration using contour coherency in CT data. IEEE Trans Med Imaging. 2006;25(3):324–334.
Yezzi A, Zöllei L, Kapur T. A variational framework for integrating segmentation and registration through active contours. Med Image Anal. 2003;7:171–185.
Kang Y, Engelke K, Kalender WA. A new accurate and precise 3D segmentation method for skeletal structures in volumetric CT data. IEEE Trans Med Imaging. 2003;22(5):586–598.
Mastmeyer A, Engelke K, Fuchs C, et al. A hierarchical 3D segmentation method and the definition of the vertebral body coordinate system for QCT of the lumbar spine. Med Image Anal. 2006; 10:560–577.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Museyko, O., Eisa, F., Hess, A., Zerfass, P., Kalender, W., Engelke, K. (2009). Binary Segmentation Masks for Registration of Bone Structures in CT Images. In: Meinzer, HP., Deserno, T.M., Handels, H., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2009. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93860-6_23
Download citation
DOI: https://doi.org/10.1007/978-3-540-93860-6_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-93859-0
Online ISBN: 978-3-540-93860-6
eBook Packages: Computer Science and Engineering (German Language)